Journal articles on the topic 'Bearings (Machinery) – Vibration – Mathematical models'
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1
Brito Junior, Geraldo Carvalho, Roberto Dalledone Machado, and Anselmo Chaves Neto. "Using Simplified Models to Assist Fault Detection and Diagnosis in Large Hydrogenerators." International Journal of Rotating Machinery 2017 (2017): 1–18. http://dx.doi.org/10.1155/2017/9258456.
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Based on experimental evidence collected in a set of twenty 700 MW hydrogenerators, this article shows that the operating conditions of large hydrogenerators journal bearings may have unpredictable and significant changes, without apparent reasons. These changes prevent the accurate determination of bearing dynamic coefficients and make the prediction of these machines dynamic behavior unfeasible, even using refined models. This makes it difficult to differentiate the normal changes in hydrogenerators dynamics from the changes created by a fault event. To overcome such difficulty, this article proposes a back-to-basics step, the using of simplified mathematical models to assist hydrogenerators vibration monitoring and exemplifies this proposal by modeling a 700 MW hydrogenerator. A first model estimates the influence of changes in bearing operating conditions in the bearing stiffnesses, considering only the hydrodynamic effects of an isoviscous oil film with linear thickness distribution. A second model simulates hydrogenerators dynamics using only 10 degrees of freedom, giving the monitored vibrations as outputs, under normal operating conditions or in the presence of a fault. This article shows that simplified models may give satisfactory results when bearing operating conditions are properly determined, results comparable to those obtained by more refined models or by measurements in the modeled hydrogenerator.
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Liu, Jing, Linfeng Wang, Zhifeng Shi, Wennian Yu, and Huifang Xiao. "A comparison investigation of the contact models for contact and vibration features of cylindrical roller bearings." Engineering Computations 36, no. 5 (June 10, 2019): 1656–75. http://dx.doi.org/10.1108/ec-11-2018-0516.
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Purpose The purpose of this study is to investigate the contact models for contact and vibration features of cylindrical roller bearings (CRBs). CRBs are important parts of rotating machinery. The contact deformation between the roller and the raceway is an essential research topic for the CRBs. The contact deformation between the roller and the raceway can greatly affect vibration characteristics and fatigue life of the CRBs. In this investigation, six different methods are adopted to calculate the contact deformation, contact area width and contact stress between the roller and raceways of a CRB. Design/methodology/approach In this paper, the contact deformations and the contact stiffnesses between the roller and the raceway of a CRB obtained by various well-known empirical methods (Lundberg’s, Palmgren’s, Houpert’s, Cheng’s and Hertzian methods) are directly compared with those by the finite element (FE) method. A two degree-of-freedom (2 DOF) dynamic model of the CRB is applied to investigate the effects of the contact stiffness obtained by different line contact deformation calculation methods on the vibration characteristics, such as the root mean square (RMS), the peak to peak (PTP), the crest factor and the kurtosis of the displacement, velocity and acceleration of the inner raceway. Findings The computational results show that different calculation methods for the contact deformations between rollers and raceways have significant effects on the vibrations of the CRB. It is found that that the differences of computational results obtained by Palmgren’s and Lundberg’s models with respect to the FE method are smaller than those by the other three methods, i.e. Houpert’s, Cheng’s and Hertzain models. The amplitude and peak frequency of the frequency response functions from Palmgren’s method are much more similar to those from the finite element method. The above results indicate that Palmgren’s method is a better calculation method for predicting the contact deformations and dynamics of the CRBs. Originality/value This work adopts six different methods to calculate the contact deformation, contact area width and contact stress between the roller and raceways of a CRB. Moreover, a vibration model of a CRB is used to investigate the effect of contact stiffness obtained by the above methods on the vibrations of the CRB. The works can give some guidance for the accurate analytical method for calculating the contact deformations between rollers and raceways and the vibrations of the CRB.
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Veselovska, Nataliya, Olha Yalina, and Vasyliy Yanishevskiy. "DEVELOPMENT OF AN ALGORITHM FOR DIAGNOSING DENTAL DEFECTS IN REDUCERS OF SELF-PROPELLED AGRICULTURAL MACHINES." ENGINEERING, ENERGY, TRANSPORT AIC, no. 3(110) (October 30, 2020): 16–23. http://dx.doi.org/10.37128/2520-6168-2020-3-2.
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Intensive use of agricultural production technologies has recognized the intensive characteristics of agricultural producers, which allowed to present the need for frequent diagnostics, maintenance and repair. This transition is due to objective trends in the development of agricultural machinery. The solution to this problem involves the development and creation of effective tools for monitoring and diagnosing the state of the transmission elements of agricultural machinery; assessment of the value of the residual life of individual elements of the system and the study of energy conversion processes in these elements; construction of mathematical models on the basis of which it is possible to predict the occurrence of dangerous damage depending on the operating conditions of the equipment. Diagnostic means must ensure the assessment of the condition of the working surfaces of the interacting transmission elements, control of wear of their surfaces and assessment of the performance of the unit as a whole or the kinematic pair without their disassembly during operation. The time of collection of diagnostic information and allocation of informative signs and parameters of signals should be minimized. Control methods should be as simple as possible, and the means that implement them - compact, with built-in algorithms for information processing and decision-making. The most informative parameter that carries the maximum information about the state of the unit of a working machine or unit is mechanical oscillations (vibrations) - elastic waves propagating in continuous media. Measurement of vibroacoustic characteristics on bearing supports of mechanisms allows to recognize such defects and damages as imbalance and skew of shafts; damage to plain and rolling bearings; damage to gears in gears; damage to couplings; damage to electrical machines. With the systematic use of modern diagnostic methods it is possible to avoid serious damage to the transmission elements and reduce operating costs for maintenance of agricultural machinery due to the fact that the repair is carried out only when the measurement results indicate its need.
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Zarraga, Ondiz, Imanol Sarría, Jon García-Barruetabeña, and Fernando Cortés. "An Analysis of the Dynamical Behaviour of Systems with Fractional Damping for Mechanical Engineering Applications." Symmetry 11, no. 12 (December 11, 2019): 1499. http://dx.doi.org/10.3390/sym11121499.
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Fractional derivative models are widely used to easily characterise more complex damping behaviour than the viscous one, although the underlying properties are not trivial. Several studies about the mathematical properties can be found, but are usually far from the most daily applications. Thus, this paper studies the properties of structural systems whose damping is represented by a fractional model from the point of view of a mechanical engineer. First, a single-degree-of-freedom system with fractional damping is analysed. Specifically, the distribution of the poles and the dynamic response to several excitations is studied for different model parameter values highlighting dissimilarities from systems with conventional viscous damping. In fact, thanks to fractional models, particular behaviours are observed that cannot be reproduced by classical ones. Finally, the dynamics of a machine shaft supported by two bearings presenting fractional damping is analysed. The study is carried out by the Finite Element method, deriving in a system with symmetric matrices. Eigenvalues and eigenvectors are obtained by means of an iterative method, and the effect of damping is visualised on the mode shapes. In addition, the response to a perturbation is computed, revealing the influence of the model parameters on the resulting vibration.
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Amin, A. K. M. Nurul, Fawaz Mohsen Abdullah, Muammer Din Arif, and Israd H. Jaafar. "Mathematical Model for Chip Serration Frequency in Turning of Stainless Steel with Magnetic Damping from Bottom of Tool Shank." Applied Mechanics and Materials 393 (September 2013): 108–14. http://dx.doi.org/10.4028/www.scientific.net/amm.393.108.
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Chatter, a violent and often unpredictable relative oscillatory motion between the tool and work-piece, is a serious concern in turning operations. Its occurrence is usually associated with a loud monotonous sound and usually results in increased surface roughness, reduced material removal rates, shortened tool life, and damaged machine-tool bearings. The established theories for chatter are very limited in scope and are often contradicted by empirical evidences. Therefore, chatter avoidance in the past has relied on inefficient techniques like limiting material removal rates or expensive setups such as actuators and ultrasonic vibration damping systems. However, a deeper investigation into chatter formation reveals that chip morphology and segmentation play a significant role during the incidence of chatter. The novel Resonance theory of chatter combines the concept of mode coupling of the machining setup and serrated chip formation, to explain and predict chatter. To validate the postulates of this theory, models for chip serration frequency are essential. At the same time, a reliable and economical chatter control method is required. With this goal, the current research work has developed an empirical mathematical model of chip serration frequency in turning of stainless steel AISI 304 using Response Surface Methodology (RSM). Also, it investigated the influence of damping provided by magnetic field from a permanent ferrite magnet placed beneath the tool shank. The developed chip serration model is in good accord with the experimental data, demonstrating that the empirical model could be used for further chip morphology and chatter analyses.
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Vania, A., and P. Pennacchi. "Effects of the Hot Alignment of a Power Unit on Oil-Whip Instability Phenomena." International Journal of Rotating Machinery 2010 (2010): 1–12. http://dx.doi.org/10.1155/2010/385947.
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This paper shows the results of the analysis of the dynamic behaviour of a power unit, whose shaft-train alignment was significantly influenced by the machine thermal state, that was affected in operating condition by high subsynchronous vibrations caused by oil-whip instability phenomena. The dynamic stiffness coefficients of the oil-film journal bearings of the generator were evaluated considering the critical average journal positions that caused the instability onsets. By including these bearing coefficients in a mathematical model of the fully assembled machine, the real part of the eigenvalue associated with the first balance resonance of the generator rotor became positive. This paper shows the successful results obtained by combining diagnostic techniques based on mathematical models of journal bearings and shaft train with detailed analyses of monitoring data aimed to investigate the effects of the hot alignment of rotating machines on the occurrence of oil-whip instability onsets.
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Ahmed, Elhaj A. I., and Li Shusen. "Optimization of Factors Affecting Vibration Characteristics of Unbalance Response for Machine Motorized Spindle Using Response Surface Method." Mathematical Problems in Engineering 2019 (February 10, 2019): 1–12. http://dx.doi.org/10.1155/2019/1845056.
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In this study, the response surface (RS) method and forced rotordynamic analyses together with Finite-Element-Analysis (FEA) have been established to optimize the factors affecting the vibration characteristics. The spindle specification, bearings locations, cutting force, and motor-rotor unbalance mass are proposed to represent the design factors and then they are utilized to develop Machine Motorized Spindle (MMS). The FEA-based Design of Experiment (DOE) is adopted to simulate the output responses with the input factors, wherein these DOE design points are used to carry out the RS models to visualize more obvious factors affecting the dynamic characteristics of MMS. The sensitivities of these factors and their contributions to the vibration of imbalance response have been evaluated by using the RS models. The simulation results show that the motor-rotor shaft inner diameter, the distance of the back bearing location, and the rotating unbalance-mass are highly sensitive to the vibration characteristics compared to the other factors. It is found that more than two-fifths of total vibration response amplitude has been conducted by induced rotating imbalance mass. The results also showed that the proposed factors optimization method is practicable and effective in improving the vibration response characteristics.
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Zmarzły, Paweł. "Mathematical model of the impact assessment of roughness and waviness deviations of races surfaces of rolling bearings on the level of generated vibration." Mechanik 92, no. 1 (January 14, 2019): 35–37. http://dx.doi.org/10.17814/mechanik.2019.1.5.
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The article presents mathematical models allowing to describe the level of vibration generated by ball bearings 6304-2z type depending on the value of roughness and waviness deviations of inner and outer bearings races. This models will allow to estimate what type of shape deviations have dominant influence on the vibration level generated in specific frequency ranges.
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Cole, Matthew O. T. "On stability of rotordynamic systems with rotor–stator contact interaction." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 464, no. 2100 (August 29, 2008): 3353–75. http://dx.doi.org/10.1098/rspa.2008.0237.
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In machine systems where a rotor spins within a finite clearance space supported by bearings, contact between the rotor and its surround can result in persistent coupled vibration of the rotor and stator. When the vibration response is driven predominantly by friction forces, rotordynamic stability becomes a serious issue. This paper introduces a theory for model-based verification of dynamic stability in rotor systems with stator contact and rub. Generalized multi-degree-of-freedom linear models of rotor and stator lateral vibration are considered, combined with contact models that account for finite clearance and Coulomb friction. State-space conditions for global stability as well as stability of contact-free synchronous whirl responses are derived using Lyapunov's direct method. This leads to feasibility problems involving matrix inequalities that can be quickly verified using numerical routines for convex optimization. Parametric studies involving flexible rotor models indicate that tight bounds on regions of stability can be obtained. A case study involving a realistic machine model illustrates how design optimization based on the theory might be used to overcome instability problems in real machines.
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Xiao, Long Xue, Guo Qing Wu, and Xu Dong Zhang. "Modal Analysis of Maglev Linear Feed Unit." Applied Mechanics and Materials 150 (January 2012): 205–10. http://dx.doi.org/10.4028/www.scientific.net/amm.150.205.
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The structural and working principle of a kind of maglev linear feed unit for CNC engraving and milling machine tools are presented, and its mathematical model is analyzed, then its model of vibration is established in this paper. The modal analysis is made, the natural frequency is calculated with its vibration models, and the influence on the natural frequency of electromagnetic levitation bearing unit, which is caused by stiffness and damping coefficients of electromagnetic levitation bearing, is analyzed respectively by means of ANSYS software. The calculation and analysis presented in this paper can help us design the structure of the maglev linear feed unit for CNC engraving and milling machine tools, and can also establish a solid foundation for further etailed dynamics analysis.
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Muszynska, Agnes. "Vibrational Diagnostics of Rotating Machinery Malfunctions." International Journal of Rotating Machinery 1, no. 3-4 (1995): 237–66. http://dx.doi.org/10.1155/s1023621x95000108.
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This paper outlines rotating machinery malfunction diagnostics using vibration data in correlation with operational process data. The advantages of vibration monitoring systems as a part of preventive/predictive maintenance programs are emphasized. After presenting basic principles of machinery diagnostics, several specific malfunction symptoms supported by simple mathematical models are given. These malfunctions include unbalance, excessive radial load, rotor-to-stator rubbing, fluid-induced vibrations, loose stationary and rotating parts, coupled torsional/lateral vibration excitation, and rotor cracking. The experimental results and actual field data illustrate the rotor vibration responses for individual malfunctions. Application of synchronous and nonsynchronous perturbation testing used for identification of basic dynamic characteristics of rotors is presented. Future advancements in vibration monitoring and diagnostics of rotating machinery health are discussed. In the Appendix, basic instrumentation for machine monitoring is outlined.
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Zmarzły, Paweł. "Multi-Dimensional Mathematical Wear Models of Vibration Generated by Rolling Ball Bearings Made of AISI 52100 Bearing Steel." Materials 13, no. 23 (November 29, 2020): 5440. http://dx.doi.org/10.3390/ma13235440.
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The paper features the development of multi-dimensional mathematical models used for evaluating the impact of selected factors on the vibration generated by 6304ZZ type rolling ball bearings from three manufacturers in the aspect of the wear process. The bearings were manufactured of AISI 52100 bearing steel. The analyzed factors included the inner and outer raceways’ roundness and waviness deviations, radial clearance and the total curvature ratio. The models were developed for vibration recorded in three frequency ranges: 50–300 Hz, 300–1800 Hz and 1800–10,000 Hz. The paper includes a specification of the principles of operation of innovative measuring systems intended for testing bearing vibration, raceway geometries and radial clearance. Furthermore, it features a specification of particular stages of the multi-dimensional mathematical models’ development and verification. Testing with the purpose of statistical evaluation of the analyzed factors is also presented. The test results and mathematical models indicate that the inner raceway’s waviness deviation had a dominant impact on the vibration examined in all frequencies. The roundness and waviness deviation of bearing raceways made of AISI 52100 steel propagates the bearing wear process.
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Medeiros, Everton C., Airton Nabarrete, Marcela A. Cruchaga, Willy R. P. Mendonca, and Mauro H. Mathias. "Numerical and Experimental Evaluation of Hydrodynamic Bearings Applied to a Jeffcott Test Bench." International Journal of Acoustics and Vibration 26, no. 1 (March 30, 2021): 64–69. http://dx.doi.org/10.20855/ijav.2020.25.11732.
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Merging analytical and numerical models with experimental results improve the behaviour predictions of mechanical elements applied to rotor machinery, such as the bearings. This work aims to present the design of a hydrodynamic bearing prototype, a comparison and validation between the numerical and experimental results of critical speeds, and the differences of behaviour when the bush geometries and lubrication are changed. The bush geometries and the fluid film properties are analysed by measuring the dynamic behaviour of a rotor supported by these bearings. The experimental evaluation is based on measuring the Jeffcott test bench supported in a pair of bearings, showing the anisotropic behaviour caused by the stiffness difference in horizontal and vertical directions. It also presents an optimization of bushings for isotropic conditions when they were changed for different geometries (elliptical, offset halves) and different materials with boundary lubrication. This detailed study shows how the dynamic behaviour of rotating machinery can be predicted using numerical models and its validation by a test rig. Results also show how the vibration occurs if the bushes geometries are modified or its lubrication condition is changed.
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Nistane, Vinod M. "Comparative performance of prognostics for remaining useful life of bearing." Noise & Vibration Worldwide 51, no. 11 (August 12, 2020): 208–22. http://dx.doi.org/10.1177/0957456520947989.
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The frequent failure components in rotary machinery are the rolling element bearings as it is important for prognostics of rolling element bearings. In this study, the data-driven technique was used to develop the prognostic models based on particle swarm optimization techniques. These models apply to estimate the rolling element bearing degradation and predict remaining useful life. Initially, the fault features were extracted by processing the vibration signals through wavelet packet decomposition based on the intensifying impulsive characteristics and superiority of features. Health indicators evaluate from fault features. The prognostic models are developed with the following approaches: Gated recurrent neural network, classification and regression tree, and Autoregressive-Moving Average models. Performances of models are verified on the basis of error in prediction. To verify the suggested methodology, an experiment on normal and faulty bearings was conducted using a bearing test rig. Experimental results clarify that the prognostic algorithms predict bearing remaining useful life with significant robustness. Outperformance of the proposed method and conformation of degree of accuracy from results indicate that remaining useful life is conjectured as inference compared with the published literature.
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Martynenko, Gennadii. "APPLICATION OF NONLINEAR MODELS FOR A WELL-DEFINED DESCRIPTION OF THE DYNAMICS OF ROTORS IN MAGNETIC BEARINGS." EUREKA: Physics and Engineering 3 (May 31, 2016): 3–12. http://dx.doi.org/10.21303/2461-4262.2016.00074.
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A research report has been submitted. It deals with implementing a method for a mathematical description of the nonlinear dynamics of rotors in magnetic bearings of different types (passive and active). The method is based on Lagrange-Maxwell differential equations in a form similar to that of Routh equations in mechanics. The mathematical models account for such nonlinearities as the nonlinear dependencies of magnetic forces on gaps in passive and active magnetic bearings and on currents in the windings of electromagnets; nonlinearities related to the inductances in coils; the geometric link between the electromagnets in one AMB and the link between all AMBs in one rotor, which results in relatedness of processes in orthogonal directions, and other factors. The suggested approach made it possible to detect and investigate different phenomena in nonlinear rotor dynamics. The method adequacy has been confirmed experimentally on a laboratory setup, which is a prototype of a complete combined magnetic-electromagnetic suspension in small-size rotor machinery. Different variants of linearizing the equations of motion have been considered. They provide for both linearization of restoring magnetic or electromagnetic forces in passive and active magnetic bearings, and exclusion of nonlinear motion equation terms. Calculation results for several linearization variants have been obtained. An appraisal of results identified the drawbacks of linearized mathematical models and allowed drawing a conclusion on the necessity of applying nonlinear models for a well-defined description of the dynamics of rotor systems with magnetic bearings.
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Saucedo-Dorantes, Juan Jose, Miguel Delgado-Prieto, Juan Antonio Ortega-Redondo, Roque Alfredo Osornio-Rios, and Rene de Jesus Romero-Troncoso. "Multiple-Fault Detection Methodology Based on Vibration and Current Analysis Applied to Bearings in Induction Motors and Gearboxes on the Kinematic Chain." Shock and Vibration 2016 (2016): 1–13. http://dx.doi.org/10.1155/2016/5467643.
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Gearboxes and induction motors are important components in industrial applications and their monitoring condition is critical in the industrial sector so as to reduce costs and maintenance downtimes. There are several techniques associated with the fault diagnosis in rotating machinery; however, vibration and stator currents analysis are commonly used due to their proven reliability. Indeed, vibration and current analysis provide fault condition information by means of the fault-related spectral component identification. This work presents a methodology based on vibration and current analysis for the diagnosis of wear in a gearbox and the detection of bearing defect in an induction motor both linked to the same kinematic chain; besides, the location of the fault-related components for analysis is supported by the corresponding theoretical models. The theoretical models are based on calculation of characteristic gearbox and bearings fault frequencies, in order to locate the spectral components of the faults. In this work, the influence of vibrations over the system is observed by performing motor current signal analysis to detect the presence of faults. The obtained results show the feasibility of detecting multiple faults in a kinematic chain, making the proposed methodology suitable to be used in the application of industrial machinery diagnosis.
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Zhao, Huimin, Rui Yao, Ling Xu, Yu Yuan, Guangyu Li, and Wu Deng. "Study on a Novel Fault Damage Degree Identification Method Using High-Order Differential Mathematical Morphology Gradient Spectrum Entropy." Entropy 20, no. 9 (September 7, 2018): 682. http://dx.doi.org/10.3390/e20090682.
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A damage degree identification method based on high-order difference mathematical morphology gradient spectrum entropy (HMGSEDI) is proposed in this paper to solve the problem that fault signal of rolling bearings are weak and difficult to be quantitatively measured. In the HMGSEDI method, on the basis of mathematical morphology gradient spectrum and spectrum entropy, the changing scale influence of structure elements to damage degree identification is thoroughly analyzed to determine its optimal scale range. The high-order difference mathematical morphology gradient spectrum entropy is then defined in order to quantitatively describe the fault damage degree of bearing. The discrimination concept of fault damage degree is defined to quantitatively describe the difference between the high-order differential mathematical entropy and the general mathematical morphology entropy in order to propose a fault damage degree identification method. The vibration signal of motors under no-load and load states are used to testify the effectiveness of the proposed HMGSEDI method. The experiment shows that high-order differential mathematical morphology entropy can more effectively identify the fault damage degree of bearings and the identification accuracy of fault damage degree can be greatly improved. Therefore, the HMGSEDI method is an effective quantitative fault damage degree identification method, and provides a new way to identify fault damage degree and fault prediction of rotating machinery.
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Gimaltdinov, Il'dus, Bulat Ziganshin, Ilgiz Galiev, Andrey Dmitriev, Al'bert Muhametshin, and Aleksandr Gricenko. "PREVENTIVE MAINTENANCE STRATEGY FOR CRUSHING EQUIPMENT." Vestnik of Kazan State Agrarian University 15, no. 3 (November 30, 2020): 71–76. http://dx.doi.org/10.12737/2073-0462-2020-71-76.
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The research was carried out in order to develop a mathematical model and a diagnostic complex to determine the residual life of the rotor bearings of hammer crushers. Residual life information is essential for proactive maintenance and to prevent equipment crashes. To achieve this goal, Kazan State Agrarian University (Republic of Tatarstan) carried out calibration studies of the dependence of the diagnostic parameters of vibration on the value of the radial clearances of the bearings. 3610 bearings with different radial clearances (0.02 mm, 0.08 mm, 0.13 mm, 0.2 mm, 0.27 mm) were alternately installed on the rotor of the KD-2 hammer mill, from the drive pulley side and from the fan side) and recorded the vibration parameters. The information was read using a piezoelectric sensor. Signal processing was performed using a VVM-201 vibrometer. The results of mathematical processing of these data are presented in earlier publications. To determine the change in the value of the radial clearance from the operating time in hours, retrospective studies were carried out directly in the agricultural enterprises of the Republic of Tatarstan: “Shaimurzinskoe agricultural enterprise named after A.Sh. Abdreev” of Drozhzhanovskiy region, JSC “Kiyatskoe”of Buinskiy region, the agricultural production complex “Ural”of Kukmorskiy region, etc. The average operating time of the bearings of the rotor of the hammer-type KD-2 forage grinder before the onset of a pre-failure state on the drive side was 1900 ... 2000 hours, on the fan side - 2000 ... 2100 h. Based on the results of the research, the values of the radial clearances and vibration parameters of the rolling bearings of the rotor of hammer crushers were experimentally established, the regularities of the change in the radial clearance of the rolling bearings of the rotor of hammer crushers were revealed depending on the operating time. The developed mathematical models for determining the radial clearance in the rotor bearings of the hammer crusher by vibration parameters and calculating the residual life are implemented in a diagnostic complex consisting of a commercially available VVM-201 vibrometer and a residual life attachment
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Maslen, E. H., C. K. Sortore, J. A. Va´zquez, and C. R. Knospe. "Synchronous Response Estimation in Rotating Machinery." Journal of Engineering for Gas Turbines and Power 124, no. 2 (March 26, 2002): 357–62. http://dx.doi.org/10.1115/1.1417482.
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Synchronous response estimation attempts to determine the forced response (displacement) of a rotor at critical points which cannot be measured directly. This type of prediction, if accurate and reliable, has broad potential use in the rotating machinery industry. Many machines have close clearance points on their shafts, such as seals, which can easily be damaged by excess vibration. Accurate estimates of the actual level of vibration at these points could usefully assist machine operators in troubleshooting and in protecting the equipment from expensive damage. This type of response information can be used both to generate less conservative alarm limits and, if magnetic bearings are available, to directly guide the bearing controllers in restricting the rotor motion at these critical points. It is assumed that the disturbance forces acting upon the rotor are predominantly synchronous. The response estimate is constructed using the measurable response in conjunction with an estimator gain matrix derived from a model of the transmissibilities of the rotor system. A fundamental performance bound is established based on the single-speed set of measurements by bounding the response to the unmeasurable component of the disturbance force. Acknowledging that some model uncertainty will always exist, a robust performance analysis is developed using structured singular value (μ) analysis techniques. Assuming some reasonable levels of uncertainty for the model parameters (natural frequencies, modal dampings, mode shapes, bearing stiffnesses, and dampings) the results of the estimator construction and analysis establish feasibility of the proposed estimation. Two reference rotor models that are representative of industrially sized machines are used to demonstrate and evaluate the estimation. The unmeasurable response estimation errors consistently lie below 25 μm for the examples examined.
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Galych, Ivan, Roman Antoshchenkov, Viktor Antoshchenkov, Igor Lukjanov, Sergey Diundik, and Oleksandr Kis. "Estimating the dynamics of a machine-tractor assembly considering the effect of the supporting surface profile." Eastern-European Journal of Enterprise Technologies 1, no. 7 (109) (February 22, 2021): 51–62. http://dx.doi.org/10.15587/1729-4061.2021.225117.
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Results of theoretical studies of dynamics of the machine-tractor assembly taking into account the influence of a bearing surface profile were presented. It was established that in the course of operation, the machine-tractor assembly is exposed to a number of external factors leading to a change of vertical loads on the chassis and the engine. Mathematical models of dynamics of a tractor and a machine and a tractor unit consisting of a tractor of pivotally connected arrangement and a trailed sower were constructed. Such models make it possible to study dynamics and oscillatory processes of multi-element units. A mathematical model of tractor wheel dynamics was formed. Speeds and angles of orientation of elements of the machine-tractor assembly in space were determined. Influence of profile of the bearing surface on the unit elements when moving in the field prepared for sowing and the field after plowing was calculated. Theoretical studies of the influence of the bearing surface profile on dynamics of the machine-tractor assembly were performed on the example of KhTZ-242K tractor and Vega-8 Profi sower (Ukraine). When moving, the sower frame has a smaller amplitude of vibration accelerations than that of the tractor. Accordingly, the tractor has higher oscillation energy because it rests on the ground through its wheels having appropriate stiffness. The sower moves with its working bodies immersed into the soil which leads to a decrease in the amplitude of oscillations. The highest energy of amplitude of oscillation accelerations of the sower frame in the vertical direction was observed at frequencies of 15.9; 23.44; 35.3 and 42.87 Hz. It was found that the increase in working speeds of agricultural units leads to the fact that oscillations of all components reach significant values. This entails an increase in dynamic loads on soil and, as a consequence, its compaction
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Inyang, Udeme, Ivan Petrunin, and Ian Jennions. "Health Condition Estimation of Bearings with Multiple Faults by a Composite Learning-Based Approach." Sensors 21, no. 13 (June 28, 2021): 4424. http://dx.doi.org/10.3390/s21134424.
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Bearings are critical components found in most rotating machinery; their health condition is of immense importance to many industries. The varied conditions and environments in which bearings operate make them prone to single and multiple faults. Widespread interest in the improvements of single fault diagnosis meant limited attention was spent on multiple fault diagnosis. However, multiple fault diagnosis poses extra challenges due to the submergence of the weak fault by the strong fault, presence of non-Gaussian noise, coupling of the frequency components, etc. A number of existing convolutional neural network models operate on a distinct feature that is not enough to assure reliable results in the presence of these challenges. In this paper, extended feature sets in three homogenous deep learning models are used for multiple fault diagnosis. This ensures a measure of diversity is introduced to the health management dataset to obtain complementary solutions from the models. The outputs of the models are fused through blending ensemble learning. Experiments using vibration datasets based on bearing multiple faults show an accuracy of 98.54%, with an improvement of 2.74% in the overall effectiveness over the single models. Compared with other technologies, the results show that this approach provides an improved generalized diagnostic capability.
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Santos, I. F., and A. Scalabrin. "Control System Design for Active Lubrication With Theoretical and Experimental Examples." Journal of Engineering for Gas Turbines and Power 125, no. 1 (December 27, 2002): 75–80. http://dx.doi.org/10.1115/1.1451757.
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This work focuses on the theoretical and experimental behavior of rigid rotors controlled by tilting-pad journal bearings with active oil injection. Initially the mathematical model of the active bearing is presented: The equations that describe the dynamics of hydraulic actuators are introduced into the equations of the lubricant, resulting in a new form of Reynolds’ equation for active lubrication. The global model of the system is obtained by coupling the equation of motion of the rigid rotor with the stiffness and damping of the active oil film. This global model is then used to design the control system of the active bearing based on root locus curves. The active system stability is analyzed by calculating its eigenvalues and frequency response curves. The theoretical and experimental results show that this kind of bearing can significantly reduce the vibration level of rotating machinery.
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Korytov, M. S., V. S. Sherbakov, and I. E. Pochekueva. "Simulation model of a chair vibration protective mechanism with a part of quasi-zero-stiffness for the operator of a road-building machine." Nauchno-tekhnicheskiy vestnik Bryanskogo gosudarstvennogo universiteta 6, no. 4 (December 25, 2020): 486–96. http://dx.doi.org/10.22281/2413-9920-2020-06-04-486-496.
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Vibrations of construction and road machinery components that occur during their operation are a harmful production factor for machine operators, therefore, their reduction can be considered a very urgent task. The main route of vibration transmission is through vibration isolation systems for the operator’s seat and cab. The easiest and most cost-effective way to isolate the operator from vibration is through his seat by reducing vibration. The simplest and most reliable vibration protection systems with one degree of freedom limited by vertical movements of the chair can be used for the chairs. Vibration protection mechanisms and systems with quasi-zero rigidity are considered promising. They provide constant static force over a certain range of movement of the object. The task of developing mathematical models describing vibration protection systems with quasi-zero rigidity is urgent. In the Matlab software package using the Simscape library for modeling physical elements, a simulation mathematical model of the vibration protection system of a chair with one degree of freedom has been developed. The base of the chair in the developed model performs harmonic sinusoidal movements. The output parameters of the developed mathematical model are the time dependences of the chair coordinates and accelerations. The blocks used in the model are described, the static force characteristics are given, given using the Hermite spline. The model includes a block of hard movement restrictions. An example of using the developed simulation mathematical model of the chair is given. The developed model makes it possible to specify both the dimensions of the quasi-zero stiffness section and the shape of the curves of the force static characteristics of the vibration protection system. It can be integrated into higher level models.
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Li, Huang, and Ji. "Bearing Fault Diagnosis with a Feature Fusion Method Based on an Ensemble Convolutional Neural Network and Deep Neural Network." Sensors 19, no. 9 (April 30, 2019): 2034. http://dx.doi.org/10.3390/s19092034.
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Rolling bearings are the core components of rotating machinery. Their health directly affects the performance, stability and life of rotating machinery. To prevent possible damage, it is necessary to detect the condition of rolling bearings for fault diagnosis. With the rapid development of intelligent fault diagnosis technology, various deep learning methods have been applied in fault diagnosis in recent years. Convolution neural networks (CNN) have shown high performance in feature extraction. However, the pooling operation of CNN can lead to the loss of much valuable information and the relationship between the whole and the part may be ignored. In this study, we proposed CNNEPDNN, a novel bearing fault diagnosis model based on ensemble deep neural network (DNN) and CNN. We firstly trained CNNEPDNN model. Each of its local networks was trained with different training datasets. The CNN used vibration sensor signals as the input, whereas the DNN used nine time-domain statistical features from bearing vibration sensor signals as the input. Each local network of CNNEPDNN extracted different features from its own trained dataset, thus we fused features with different discrimination for fault recognition. CNNEPDNN was tested under 10 fault conditions based on the bearing data from Bearing Data Center of Case Western Reserve University (CWRU). To evaluate the proposed model, four aspects were analyzed: convergence speed of training loss function, test accuracy, F-Score and the feature clustering result by t-distributed stochastic neighbor embedding (t-SNE) visualization. The training loss function of the proposed model converged more quickly than the local models under different loads. The test accuracy of the proposed model is better than that of CNN, DNN and BPNN. The F-Score value of the model is higher than that of CNN model, and the feature clustering effect of the proposed model was better than that of CNN.
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Zeng, S., J.-Q. Zhang, and H.-N. Wang. "Transient Response of Active Magnetic Bearing Rotor During Rotor Drop on Backup Bearings." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 220, no. 6 (June 1, 2006): 785–94. http://dx.doi.org/10.1243/09544062c14004.
Full textAbstract:
Backup bearing is a key safety component of the rotating machinery with the active magnetic bearings (AMBs). Owing to many unexpected reasons, the AMB rotor running at the full speed may drop onto the backup bearings. Sometimes, the full clearance whirling motion is induced, which is harmful to the machine. Therefore, it is quite important to know the transient behaviour of the AMB rotor and the backup bearing. Till date, a lot of works have been performed on the AMB rotor drop and various mathematical models were established. However, most of them took into account only the interaction between the rotor journal and the backup bearing but neglected the interaction between the shaft and the stator component. As we know, for a real AMB machinery, there should be seal components, and the clearance of the seal component is very small to avoid the leakage. If an AMB failure occurs, the interaction between the shaft and the seal component is likely to happen. Thus, it is more reasonable to include this factor into the AMB rotor drop model. The problem is addressed in this work. The previous model is extended to include the shaft-stator contact. The numerical analysis based on two sets of AMB rotor data shows that the dynamic behaviour of the AMB changes greatly, if the shaft-stator contact is considered. There is no longer an optimum support damping to prevent the harmful full clearance whirling motion, and at this time, a well-balanced AMB rotor is preferred.
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Rajczyk, Jarosław. "Modelling the Dynamic Load Process in the Building Technology Process." Applied Mechanics and Materials 405-408 (September 2013): 652–56. http://dx.doi.org/10.4028/www.scientific.net/amm.405-408.652.
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Vibration is a priority in the field of construction machinery in the process group dynamic load processing of different materials. Presented here are models with basic mathematical relationships that we utilize to describe phenomena in the task of modeling any process of dynamic loads acting on the treated medium. In the presented material, diagrams are considered necessary when dealing with specific parameters modeling of real processes of rheological effects on the body: elastic-inertial, viscous-inertial and yielding-inertial on, for example, treatments of concrete mixes.
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Guo, Zijian, Mingliang Liu, Huabin Qin, and Bing Li. "Mechanical Fault Diagnosis of a DC Motor Utilizing United Variational Mode Decomposition, SampEn, and Random Forest-SPRINT Algorithm Classifiers." Entropy 21, no. 5 (May 6, 2019): 470. http://dx.doi.org/10.3390/e21050470.
Full textAbstract:
Traditional fault diagnosis methods of DC (direct current) motors require establishing accurate mathematical models, effective state and parameter estimations, and appropriate statistical decision-making methods. However, these preconditions considerably limit traditional motor fault diagnosis methods. To address this issue, a new mechanical fault diagnosis method was proposed. Firstly, the vibration signals of motors were collected by the designed acquisition system. Subsequently, variational mode decomposition (VMD) was adopted to decompose the signal into a series of intrinsic mode functions and extract the characteristics of the vibration signals based on sample entropy. Finally, a united random forest improvement based on a SPRINT algorithm was employed to identify vibration signals of rotating machinery, and each branch tree was trained by applying different bootstrap sample sets. As the results reveal, the proposed fault diagnosis method is featured with good generalization performance, as the recognition rate of samples is more than 90%. Compared with the traditional neural network, data-heavy parameter optimization processes are avoided in this method. Therefore, the VMD-SampEn-RF-based method proposed in this paper performs well in fault diagnosis of DC motors, providing new ideas for future fault diagnoses of rotating machinery.
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Yuan, Qiang, Yu Sun, Rui-ping Zhou, Xiao-fei Wen, and Liang-xiong Dong. "Prediction and analysis of bearing vibration signal with a novel gray combination model." Advances in Mechanical Engineering 12, no. 5 (May 2020): 168781402091924. http://dx.doi.org/10.1177/1687814020919241.
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Bearings are the core components of ship propulsion shafting, and effective prediction of their working condition is crucial for reliable operation of the shaft system. Shafting vibration signals can accurately represent the running condition of bearings. Therefore, in this article, we propose a new model that can reliably predict the vibration signal of bearings. The proposed method is a combination of a fuzzy-modified Markov model with gray error based on particle swarm optimization (PGFM (1,1)). First, particle swarm optimization was used to optimize and analyze the three related parameters in the gray model (GM (1,1)) that affect the data fitting accuracy, to improve the data fitting ability of GM (1,1) and form a GM (1,1) based on particle swarm optimization, which is called PGM (1,1). Second, considering that the influence of historical relative errors generated by data fitting on subsequent data prediction cannot be expressed quantitatively, the fuzzy mathematical theory was introduced to make fuzzy corrections to the historical errors. Finally, a Markov model is combined to predict the next development state of bearing vibration signals and form the PGFM (1,1). In this study, the traditional predictions of GM (1,1), PGM (1,1), and newly proposed PGFM (1,1) are carried out on the same set of bearing vibration data, to make up for the defects of the original model layer by layer and form a set of perfect forecast system models. The results show that the predictions of PGM (1,1) and PGFM (1,1) are more accurate and reliable than the original GM (1,1). Hence, they can be helpful in the design of practical engineering equipment.
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Li, Heng, Qing Zhang, Xianrong Qin, and Sun Yuantao. "Raw vibration signal pattern recognition with automatic hyper-parameter-optimized convolutional neural network for bearing fault diagnosis." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 234, no. 1 (September 19, 2019): 343–60. http://dx.doi.org/10.1177/0954406219875756.
Full textAbstract:
Bearing fault diagnosis is of great significance for evaluating the reliability of machines because bearings are the critical components in rotating machinery and are prone to failure. Because of non-stationarity and the low signal-noise rate of raw vibration signals, traditional fault diagnosis methods often construct representative fault features via the technologies of feature engineering. These methods rely heavily on expertise and are inadequate in actual applications. Recently, methods based on convolutional neural networks have been studied extensively to relieve the demands of hand-crafted feature extraction and feature selection. However, the raw vibration signal is rarely taken as a direct input. This study combines a convolutional neural network with automatic hyper-parametric optimization and proposes two deep learning models for time-series pattern recognition to achieve “end-to-end” bearing fault diagnosis: a one-dimensional-convolutional neural network and a dilated convolutional neural network. The architecture of the two models are tweaked by automatic optimization rather than manual trial or grid search. Further, we try to figure out the inner operating mechanism of the proposed methods by visualizing the automatically learned features. The proposed methods are applied to diagnose roller bearing faults on a benchmark experiment and a prototype experiment. The results verify that our methods can achieve better performance than other intelligent methods via a Gaussian-noise test.
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Wang, Xiaoqian, Dali Sheng, Jinlian Deng, Wei Zhang, Jie Cai, Weisheng Zhao, and Jiawei Xiang. "Kernel Regression Residual Decomposition Method to Detect Rolling Element Bearing Faults." Mathematical Problems in Engineering 2021 (April 28, 2021): 1–10. http://dx.doi.org/10.1155/2021/5523098.
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The raw vibration signal carries a great deal of information representing the mechanical equipment's health conditions. However, in the working condition, the vibration response signals of faulty components are often characterized by the presence of different kinds of impulses, and the corresponding fault features are always immersed in heavy noises. Therefore, signal denoising is one of the most important tasks in the fault detection of mechanical components. As a time-frequency signal processing technique without the support of the strictly mathematical theory, empirical mode decomposition (EMD) has been widely applied to detect faults in mechanical systems. Kernel regression (KR) is a well-known nonparametric mathematical tool to construct a prediction model with good performance. Inspired by the basic idea of EMD, a new kernel regression residual decomposition (KRRD) method is proposed. Nonparametric Nadaraya–Watson KR and a standard deviation (SD) criterion are employed to generate a deep cascading framework including a series of high-frequency terms denoted by residual signals and a final low-frequency term represented by kernel regression signal. The soft thresholding technique is then applied to each residual signal to suppress noises. To illustrate the feasibility and the performance of the KRRD method, a numerical simulation and the faulty rolling element bearings of well-known open access data as well as the experimental investigations of the machinery simulator are performed. The fault detection results show that the proposed method enables the recognition of faults in mechanical systems. It is expected that the KRRD method might have a similar application prospect of EMD.
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Xue, Xiaoming, Nan Zhang, Suqun Cao, Wei Jiang, Jianzhong Zhou, and Liyan Liu. "New State Identification Method for Rotating Machinery under Variable Load Conditions Based on Hybrid Entropy Features and Joint Distribution Adaptation." Complexity 2020 (July 10, 2020): 1–17. http://dx.doi.org/10.1155/2020/7247195.
Full textAbstract:
Fault identification under variable operating conditions is a task of great importance and challenge for equipment health management. However, when dealing with this kind of issue, traditional fault diagnosis methods based on the assumption of the distribution coherence of the training and testing set are no longer applicable. In this paper, a novel state identification method integrated by time-frequency decomposition, multi-information entropies, and joint distribution adaptation is proposed for rolling element bearings. At first, fast ensemble empirical mode decomposition was employed to decompose the vibration signals into a collection of intrinsic mode functions, aiming at obtaining the multiscale description of the original signals. Then, hybrid entropy features that can characterize the dynamic and complexity of time series in the local space, global space, and frequency domain were extracted from each intrinsic mode function. As for the training and testing set under different load conditions, all data was mapped into a reproducing space by joint distribution adaptation to reduce the distribution discrepancies between datasets, where the pseudolabels of the testing set and the final diagnostic results were obtained by the k-nearest neighbor algorithm. Finally, five cases with the training and testing set under variable load conditions were used to demonstrate the performance of the proposed method, and comparisons with some other diagnosis models combined with the same features and other dimensionality reduction methods were also discussed. The analysis results show that the proposed method can effectively recognize the multifaults of rolling element bearings under variable load conditions with higher accuracies and has sound practicability.
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Dimarogonas, Andrew D., and Julio C. Gomez-Mancilla. "Flow-Excited Turbine Rotor Instability." International Journal of Rotating Machinery 1, no. 1 (1994): 37–51. http://dx.doi.org/10.1155/s1023621x94000047.
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The problem of steam whirl is one of the technological limits that now prohibit the development of power-generating turbomachinery substantially above GW. Due to steam flow, self-excited vibrations develop at high loads in the form of stable limit cycles that, at even higher loads, deteriorate to chaotic vibration of high amplitude.A mathematical model is developed for stability analysis and for the development of a rational stability criterion to be used at the design stage. The bearing nonlinearity is introduced in the form of high-order coefficients of a Taylor expansion of the perturbation forces for fixed-arc slider bearings and employing nonlinear pad functions for the tilting pad bearings. The flow excitation is introduced in the form of follower force gradients related to the flow and the power generated.The study of the stable and unstable limit cycles, and the stability of the system in the large, beyond the linear analysis currently utilized, is done analytically for the De Laval rotor and numerically with finite element analysis of typical turbomachinery rotors.The range of loads for which limit cycles exist was found to be substantial. This is important for the operation of large machinery because such cycles permit the operation at loads much higher than the ones that correspond to the onset of instability of the linearized system. The conditions for the limit cycle deterioration into chaotic orbit are investigated. Analytical expressions have been obtained for the different stability thresholds for the De Laval rotor.
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Kryukov, O. V., S. E. Stepanov, and A. B. Vasenin. "MODELING AND MONITORING OF THERMODYNAMIC PROCESSES IN SYNCHRONOUS ELECTRIC MOTORS." Kontrol'. Diagnostika, no. 262 (April 2020): 28–35. http://dx.doi.org/10.14489/td.2020.04.pp.028-035.
Full textAbstract:
Methods are given for the mathematical description of thermodynamic processes in the insulation of drive motors of alternating current megawatt class. The paper presents the requirements for equipping monitoring systems of the main technological equipment and electric machines, in particular, which regulate the monitoring of working capacity, reliability and safety of equipment using reliable technical and software tools. The most appropriate when choosing a monitoring model for synchronous motors is a functional diagnostic model, when using which the input actions of elementary checks are determined in advance by the working algorithm of the object, and only the composition of the controlled parameters of the diagnostic object is subject to selection. For a predictive analysis of the temperature of the windings of a synchronous machine, a three-stage heating theory is used, in which the motor is divided into a stator winding, a steel structure of the stator and a rotor. In addition, the models take into account the mechanical loads acting on the insulation of the stator windings in various modes during operation: electrodynamic, vibrational and thermomechanical. The results of the analysis of the dynamics of thermodynamic processes in the stator windings of machines with refinements related to the effects of cooling methods, the finning of the external surface of the machine, the heat sink through the frame and bearing shields, as well as the influence of a significant amount of air inside the thermal circuits of synchronous motors. For engineering calculations, algorithms for determining electrodynamic forces are recommended, taking into account simplifying assumptions that do not affect the accuracy of the practical assessment of the forces acting on the isolation of powerful machines. The determination of only some of the main components of the effects, which include the forces caused by the interaction of currents of one phase and acting on the extreme rod of the phase group in the involute part of the rod along the corresponding curves, is also justified.
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Kryukov, O. V., S. E. Stepanov, and A. B. Vasenin. "MODELING AND MONITORING OF THERMODYNAMIC PROCESSES IN SYNCHRONOUS ELECTRIC MOTORS." Kontrol'. Diagnostika, no. 262 (April 2020): 28–35. http://dx.doi.org/10.14489/td.2020.04.pp.028-035.
Full textAbstract:
Methods are given for the mathematical description of thermodynamic processes in the insulation of drive motors of alternating current megawatt class. The paper presents the requirements for equipping monitoring systems of the main technological equipment and electric machines, in particular, which regulate the monitoring of working capacity, reliability and safety of equipment using reliable technical and software tools. The most appropriate when choosing a monitoring model for synchronous motors is a functional diagnostic model, when using which the input actions of elementary checks are determined in advance by the working algorithm of the object, and only the composition of the controlled parameters of the diagnostic object is subject to selection. For a predictive analysis of the temperature of the windings of a synchronous machine, a three-stage heating theory is used, in which the motor is divided into a stator winding, a steel structure of the stator and a rotor. In addition, the models take into account the mechanical loads acting on the insulation of the stator windings in various modes during operation: electrodynamic, vibrational and thermomechanical. The results of the analysis of the dynamics of thermodynamic processes in the stator windings of machines with refinements related to the effects of cooling methods, the finning of the external surface of the machine, the heat sink through the frame and bearing shields, as well as the influence of a significant amount of air inside the thermal circuits of synchronous motors. For engineering calculations, algorithms for determining electrodynamic forces are recommended, taking into account simplifying assumptions that do not affect the accuracy of the practical assessment of the forces acting on the isolation of powerful machines. The determination of only some of the main components of the effects, which include the forces caused by the interaction of currents of one phase and acting on the extreme rod of the phase group in the involute part of the rod along the corresponding curves, is also justified.
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Xiao, Yancai, and Zhe Hua. "Misalignment Fault Prediction of Wind Turbines Based on Combined Forecasting Model." Algorithms 13, no. 3 (March 1, 2020): 56. http://dx.doi.org/10.3390/a13030056.
Full textAbstract:
Due to the harsh working environment of wind turbines, various types of faults are prone to occur during long-term operation. Misalignment faults between the gearbox and the generator are one of the latent common faults for doubly-fed wind turbines. Compared with other faults like gears and bearings, the prediction research of misalignment faults for wind turbines is relatively few. How to accurately predict its developing trend has always been a difficulty. In this paper, a combined forecasting model is proposed for misalignment fault prediction of wind turbines based on vibration and current signals. In the modelling, the improved Multivariate Grey Model (IMGM) is used to predict the deterministic trend and the Least Squares Support Vector Machine (LSSVM) optimized by quantum genetic algorithm (QGA) is adopted to predict the stochastic trend of the fault index separately, and another LSSVM optimized by QGA is used as a non-linear combiner. Multiple information of time-domain, frequency-domain and time-frequency domain of the wind turbine’s vibration or current signals are extracted as the input vectors of the combined forecasting model and the kurtosis index is regarded as the output. The simulation results show that the proposed combined model has higher prediction accuracy than the single forecasting models.
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Тихомиров, Петр, Petr Tikhomirov, Елена Лемешева, Elena Lemesheva, Николай Булхов, Nikolay Bulkhov, Анна Атрощенко, Anna Atroshchenko, Михаил Измеров, and Mikhail Izmerov. "NEUROCOMPUTER MODELING OF CONTACT RIGIDITY." Bulletin of Bryansk state technical university 2016, no. 2 (June 30, 2016): 156–66. http://dx.doi.org/10.12737/20285.
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Contact rigidity of a joint is one of the main criteria of operability of forest cars. It defines vibration activity and durability of the tightened bolted connections therefore its assessment will allow to predict behavior of technical systems. In work the technique of an assessment of contact rigidity by means of the nerocomputer modeling allowing to consider parameters of quality of a blanket is presented. Results of re-searches allowed to receive mathematical models for contact rigidity.
In the paper there is presented a procedure of contact rigidity estimate with the aid of neurocomputer modeling. A contact rigidity of a joint is one of the basic criteria of machine and mechanism capacity for work. It defines vibration activity and strength of tightened bolted connections therefore its estimate will allow forecasting the behavior of technical systems. Neurocomputer modeling is a promising method allowing taking into account quality parameters of a surface layer of machinery at the analysis of a deformed state.
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Yang, Xiongjun, Han Su, Lijun Liu, and Ying Lei. "Identification of the nonlinear characteristics of rubber bearings in model-free base-isolated buildings using partial measurements of seismic responses." Journal of Low Frequency Noise, Vibration and Active Control 39, no. 3 (April 16, 2019): 690–703. http://dx.doi.org/10.1177/1461348419843385.
Full textAbstract:
Rubber-bearing isolation is one of the most successfully and widely used isolation technologies to provide lateral flexibility and energy dissipation capacity for reducing structural vibration and protecting the superstructure from damage. The seismic performance of the base-isolated structures partly depends on the nonlinear characteristics of the base isolation system. However, it is hard to establish proper mathematical models for the nonlinear hysteretic behaviors of base isolation due to the complexities of nonlinearities. Consequently, it is strongly desired to develop model-free methodologies for the nonlinear hysteretic performance identification with no assumption on the nonlinear hysteretic models of base isolation. In this paper, a novel method is proposed for this purpose. Firstly, the base isolation is in the linear state when the structure is under the weak earthquake, the restoring force is only provided by linear stiffness and viscous damping of base isolation, and the structural physical parameters can be estimated based on the extended Kalman filter approach. Then, the base isolation is in the nonlinear state when the structure is under the strong earthquake. The nonlinear hysteretic restoring forces from base isolation are treated as “unknown fictitious inputs” to the corresponding structural systems without base isolation. The generalized Kalman filter with unknown input algorithm is adopted for the simultaneous identification of the corresponding structural systems and the hysteretic restoring force of base isolation using only partial structural responses. No information about the structure is needed, and the responses at the location of the base isolation are not required, the proposed method is capable of identifying nonlinear characteristics of base isolation by the direct use of partial structural dynamic response. To validate the performances of the proposed method, some numerical simulation examples of identifying nonlinear hysteretic restoring forces of base isolation in different models are used.
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Snitynskyy, Volodymyr, Volodymyr Burtak, Bohdan Diveyev, Orest Horbay, Ruslan Humenyuk, and Ivan Kernytskyy. "Dynamic properties of screw-bolts connections of sowing machine." Przegląd Naukowy Inżynieria i Kształtowanie Środowiska 28, no. 4 (December 29, 2019): 584–93. http://dx.doi.org/10.22630/pniks.2019.28.4.53.
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A vehicle is a complicated system under the influence of vibration caused by an inequality of the road surface, variable speed, unbalance of the rotating elements. The main factors influencing the relaxation of threaded connections (TC) are the amplitude, frequency and gradient of vibration. Although the frequencies of these oscillations are distributed over a wide range, the general effects of dynamic loading on bolted connections are similar. Main effects: (1) loosening the nut/bolt and (2) failure due to fatigue failure. The analysis of the technological process of agricultural machinery shows that the main external factors influencing their work are the profile of the surface of the field, the hardness and moisture of the soil, the speed of the unit, the instability of the engine, the traction of the wheels of the tractor and others. To study the integrity of TC, which is tested on the stand, consider the design scheme of nonlinear oscillations of the design in the presence of gaps in the TC. The study was conducted in two modes of movement of the drill: with tightened bolts and weakened bolts. For the survey, the method of spectral analysis of multidimensional periodically non-stationary random signals was used. In the process of testing, the dynamic loading of bolted joints installed on the respective knots and components of the drill was evaluated. From the conducted research it follows that the maximum vibrations acting on the TC of the drill may be in the vicinity of high-frequency resonances of TC. In parallel, nonlinear mathematical models of the oscillations of the seeder and the weakened TC were developed. The theoretical results qualitatively correspond to the experimental data.
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Grigore, Jan Cristian. "The Methods to Study the Influence of the Clearance in the Case of Great Speeds and Small Speeds." Advanced Materials Research 837 (November 2013): 88–92. http://dx.doi.org/10.4028/www.scientific.net/amr.837.88.
Full textAbstract:
In kinematic couplings, clearances are inevitable for their operation. The size of these clearances but as a consequence of use, causes a malfunction of the mechanism to which it belongs. The law of motion of driveline changes, big clearances, non-technological system causes vibration, leading to discomfort, uncertainty, and thus reach its degradation. In the paper we shall make a few of geometric and mechanical type considerations about the clearances in the linkages, linkages planes with joint rotation links. Based on mathematical algorithm developed and applied crank mechanism, the model presented in [1], this paper scientifically developed mathematical model, proposing mathematical models to study the influence of the size of the clearance in general dynamic calculation mechanisms. Mechanism considered is crank connecting rod mechanism with clearance cinematic coupling between rod and crank rotation. The paper makes a study of the influence on the dynamic behavior of the crank rod mechanism at high speeds, but also general method algorithm is developed and accurate method to assess the dynamic behavior of multi-body mechanism. The first case is considered a constant angular speed motor and thus determine the elemental expressions that establish the mechanism position, velocity and acceleration expressions in the two directions heads elements. Finally we obtain the expression of the normal reaction force, as well as position expression that defines its angle. With reaction force can specify phase (contact, flight, impact) [1], the behavior of the journal. For the case of general method - the method multi-body - the exact method are established liaison relationships between the parameters , write matrices , inertia matrix. Use Lagrange equations, if non-holonomic constraints. Matrix differential equation of motion is written and it can be solved numerically using Runge-Kutta method of order four. Of the iterative method, we obtain the parameters used in calculating the reaction force expression that can be evaluated accurately in journal bearings behaviour. Any would be their source of appearance, they usually produce unwished effects during the mechanisms functioning.
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Hoffmann, Robert, Oliver Munz, Tomasz Pronobis, Enrico Barth, and Robert Liebich. "A valid method of gas foil bearing parameter estimation: A model anchored on experimental data." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 232, no. 24 (August 30, 2016): 4510–27. http://dx.doi.org/10.1177/0954406216667966.
Full textAbstract:
Gas foil bearings are a smart green technology and suitable for the next generation of small turbo machinery e.g. turbochargers, micro gas turbines, range extenders and compressors of fuel cells. A combination of low power loss, high speed operation and the omission of an oil system are the major advantages. To enable access to this technology, it is essential to evaluate critical speeds and onset speeds of subharmonic vibration of the rotor system in the first design stage. Hence, robust and valid models are necessary, which correctly describe the fluid structure interaction between the lubrication film and the elastic bearing structure. In the past three decades several experimental and numerical investigations of bearing parameters have been published. But the number of sophisticated models is small and there is still a lack of validation towards experimental works. To make it easy for designers dealing with this issue, the bearing parameters are often linearised about certain operating points. In this paper a method for calculating linearised bearing parameters (stiffness and damping) of gas foil bearing is presented. Experimental data are used for validation of the model. The linearised stiffness and damping values are calculated using a perturbation method. The pressure field is coupled with a two-dimensional plate model, while the non-linear bump structure is simplified by a link-spring model. It includes Coulomb friction effects inside the elastic corrugated structure and captures the interaction between the single bumps. For solving the separated perturbed Reynolds equation a static stiffness is used for the 0. order equation (stationary case) and a dynamic stiffness is applied for 1. order equation (dynamic case). Therefore, an additional dynamic structural model is applied to calculate the dynamic stiffness. The results depend on the load level and friction state of each bump. Different case studies including the impact of clearance, frictional contacts and the comparison of a linear and non-linear structure are carried out for infinitesimal perturbations. The results show, that the linear structure underestimates main and cross-coupling effects. The impact of the clearance is notable, while the impact of the overall frictional contacts is small due to relatively small loadings. The infinitely small perturbation model is adapted to the experimental setup by using a superposition of two resulting bearing parameters identifications of two total loadings including shaker forces. Due to this adaptation a good correlation with the experimental results of the bearing parameters is achieved.
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Shi, Junchuan, Tianyu Yu, Kai Goebel, and Dazhong Wu. "Remaining Useful Life Prediction of Bearings Using Ensemble Learning: The Impact of Diversity in Base Learners and Features." Journal of Computing and Information Science in Engineering 21, no. 2 (October 13, 2020). http://dx.doi.org/10.1115/1.4048215.
Full textAbstract:
Abstract Prognostics and health management (PHM) of bearings is crucial for reducing the risk of failure and the cost of maintenance for rotating machinery. Model-based prognostic methods develop closed-form mathematical models based on underlying physics. However, the physics of complex bearing failures under varying operating conditions is not well understood yet. To complement model-based prognostics, data-driven methods have been increasingly used to predict the remaining useful life (RUL) of bearings. As opposed to other machine learning methods, ensemble learning methods can achieve higher prediction accuracy by combining multiple learning algorithms of different types. The rationale behind ensemble learning is that higher performance can be achieved by combining base learners that overestimate and underestimate the RUL of bearings. However, building an effective ensemble remains a challenge. To address this issue, the impact of diversity in base learners and extracted features in different degradation stages on the performance of ensemble learning is investigated. The degradation process of bearings is classified into three stages, including normal wear, smooth wear, and severe wear, based on the root-mean-square (RMS) of vibration signals. To evaluate the impact of diversity on prediction performance, vibration data collected from rolling element bearings was used to train predictive models. Experimental results have shown that the performance of the proposed ensemble learning method is significantly improved by selecting diverse features and base learners in different degradation stages.
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Ovy, Enaiyat Ghani. "Suppression of Rubbing in Rotating Machines by Lemon-Type Bearing." Journal of Vibration and Acoustics 141, no. 5 (June 17, 2019). http://dx.doi.org/10.1115/1.4043817.
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Rotor-to-stator or rotor-to-guide rubbing in rotating machines is a serious problem. The contact (rub and impact) between the rotor and the guide creates an excessive vibration which may lead to permanent damage of the mechanical system. In the present work, the rubbing phenomenon between the rotor and the guide is investigated by simulation and experiment. Two different types of clearance bearings are implemented, which are based on circular and lemon-type guides. Rigorous mathematical models for the lemon-type guide as well as for the traditional circular clearance bearing are derived. Then, a Jeffcott rotor model is simulated for the investigation of the rubbing behavior for the two types of bearings. The numerical model is developed in matlab simulink. For different clearances and friction levels between rotor and guide, and several initial conditions, the rubbing phenomena are studied and evaluated. Finally, a comparison between experimental and simulation work is carried out to validate the overall scenarios in this research work. Results indicate that the lemon-type bearing can reduce the likelihood of sustained rubbing, compared with the circular clearance bearing, for the considered test cases.
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Petrov, E. P. "Analytical Formulation of Friction Contact Elements for Frequency-Domain Analysis of Nonlinear Vibrations of Structures With High-Energy Rubs." Journal of Engineering for Gas Turbines and Power 141, no. 12 (November 8, 2019). http://dx.doi.org/10.1115/1.4045183.
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Abstract In gas-turbine engines and other rotating machinery structures, rubbing contact interactions can occur when the contacting components have large relative motion between components: such as in rotating bladed disk-casing rubbing contacts, and rubbing in rotor bearing and labyrinth seals. The analysis of vibrations of structures with rubbing contacts requires the development of a mathematical model and special friction contact elements that would allow for the prescribed relative motion of rubbing surfaces in addition to the motion due to vibrations of the contacting components. In the proposed paper, the formulation of the friction contact elements is developed, which includes the effects of the prescribed relative motion on the friction stick-slip transitions and, therefore, on the contact interaction forces. For a first time, the formulation is made for the frequency domain analysis of coupled rubbing and vibrational motion, using the multiharmonic representation of the vibration displacements. The formulation is made fully analytically to express the multiharmonic contact interaction forces and multiharmonic tangent stiffness matrix in an explicit analytical form allowing their calculation accurately and fast. The dependency of the friction and contact stiffness coefficients on the energy dissipated during high-energy rubbing contacts and, hence, on the corresponding increase of the contact interface temperature is included in the formulation. The efficiency of the developed friction elements is demonstrated on a set of test cases including simple models and a large-scale realistic blade.
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Yabui, Shota, Jotaro Chiba, Takafumi Suzuki, Shigeyuki Tomimatsu, and Tsuyoshi Inoue. "Analysis of Whirling Vibration Due to Morton Effect by Using Frequency Transfer Function Model in Journal Bearings." Journal of Dynamic Systems, Measurement, and Control 142, no. 4 (February 11, 2020). http://dx.doi.org/10.1115/1.4046105.
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Abstract In recent years, rotating machinery has been required to operate at high rotational speeds for high efficiency. However, with increase in the rotational speed, the rotating machinery may become unstable. One cause of unstable vibrations is the Morton effect that occurs in journal bearings. Thus, developing a mathematical model to predict the Morton effect is desirable to avoid the occurrence of such unstable vibrations. In this study, a model based on a frequency response that can quantitatively evaluate the Morton-effect-induced vibrations in rotating machinery supported by a journal bearing was developed. Experimental data were collected for modeling by using an experimental rig. Using the experimental data pertaining to the journal position in the journal bearing and temperature of the journal, a model for the Morton effect was established based on the frequency responses. From a control engineering viewpoint, the journal bearing was considered to be a proportional differential controller. In addition, the Morton-effect-induced vibrations were considered as a new bending mode of a rotating shaft, caused by thermal differences. Subsequently, the developed model was evaluated in the frequency domain. The characteristics of the vibrations, determined using the proposed model, exhibited good correlation with those corresponding to experimental data. The experimental data agreed well with the predicted results, and the results demonstrated the usefulness of the proposed method for predicting the Morton effect.
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Kanai, R. A., R. G. Desavale, and S. P. Chavan. "Experimental-Based Fault Diagnosis of Rolling Bearings Using Artificial Neural Network." Journal of Tribology 138, no. 3 (April 27, 2016). http://dx.doi.org/10.1115/1.4032525.
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In this paper, an innovative system for condition-based monitoring (CBM) using model-based estimation (MBE) and artificial neural network (ANN) is proposed. Fault diagnosis of deep groove ball bearings (DGBB) is a key machine element for stability of rotating machinery. MBE model is proposed to demonstrate and estimate the vibration characteristics of bearings. It is realized that it may be worth mentioning that the vibration analysis of damaged bearings at all the positions of a structure is difficult to obtain. For this purpose, methods have been discussed to get the utmost information to notify bearing faults. The ANN approach enables us to determine the effects of various parameters of the vibrations by conducting the experiments. The results point out that defect size, speed, load, unbalance, and clearance influence the vibrations significantly. Experimental simulated data using the MBE and ANN models of rotor–bearing are used to identify the damage diagnosis at a reasonable level of accuracy. The results of the experiments consist in constantly evaluating the performance of the bearing and thereby detecting the faults and vibration characteristics successfully. The effects of faults and vibration characteristics obtained using the experimental MBE and ANN are studied.
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Yoshimatsu, Osamu, Yoshihiro Satou, and Kenichi Shibasaki. "Rolling Bearing Diagnosis Based on CNN-LSTM and Various Condition Dataset." Annual Conference of the PHM Society 10, no. 1 (September 24, 2018). http://dx.doi.org/10.36001/phmconf.2018.v10i1.545.
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Flaking is typical failure mode in rolling bearings. Therefore, flaking diagnosis plays a critical role in condition monitoring of general rotating machinery. In recent years, there has been an increasing interest in deep learning technique for bearing flaking diagnosis, because it can learn the flaking induced vibration features with no information of bearing specifications nor that of rotating speed. However, most of the studies have only focused on laboratory data using one test rig as well as a small dataset under the limited operating condition. Accordingly, no discussion has been found on the generalization performance of the diagnostic model, i.e., availability for actual rotating machinery, in which vibration feature is affected by various operating conditions and unknown disturbance. In this study, more than 21,000 timeseries waveforms of normal and bearing flaking induced machine vibration were prepared from three types of test rig and three bearing types under various operating condition. And deep learning such as Convolutional Neural Network - Long Short-Term Memory (CNN-LSTM) models were applied to recognize flaking bearing vibration. The applied models trained with various condition data showed higher accuracy of various condition test data diagnosis than other models trained using single condition data. Furthermore, the applied diagnostic models also showed less accuracy degradation for test data in which additional artificial noise was imposed, than the models trained with single condition data.
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Ma, Meng, and Zhu Mao. "Deep wavelet sequence-based gated recurrent units for the prognosis of rotating machinery." Structural Health Monitoring, July 2, 2020, 147592172093315. http://dx.doi.org/10.1177/1475921720933155.
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Prognostics and health management (PHM) is an emerging technique which aims to improve the reliability and safety of machinery systems. Remaining useful life (RUL) prediction is the key part of PHM which provides operators how long the machine keeps working without breakdowns. In this study, a novel prognostic model is proposed for RUL prediction using deep wavelet sequence-based gated recurrent units (GRU). This proposed wavelet sequence-based gated recurrent unit (WSGRU) specifically adopts a wavelet layer and generates wavelet sequences at different scales. Since vibration signals exhibit non-stationary characteristics, wavelet analysis is thereby needed to capture both the time and frequency domain information to fully identify the degradation of the rotating components. In the proposed WSGRU, the vibration signals are decomposed into different frequency sub-bands via wavelet transformation, and then a deep GRU architecture is designed to predict the RUL taking advantage of the temporal dependencies that naturally exist in the waveforms. Experimental studies have been performed for RUL prediction of bearings with collection of vibration signals during the run-to-failure tests. The prediction results show that deep WSGRU outperforms traditional models due to the multi-level feature extraction on the transformed multiscale wavelet sequences.
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Brito, Geraldo C., Roberto D. Machado, Anselmo C. Neto, and Leonardo Y. Kimura. "A method for the experimental estimation of direct and cross-coupled dynamic coefficients of tilting-pad journal bearings of vertical hydro-generators." Structural Health Monitoring, June 22, 2021, 147592172110265. http://dx.doi.org/10.1177/14759217211026593.
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This article presents a method to experimentally estimate the direct and cross-coupled dynamic coefficients of tilting-pad journal bearings of vertical hydro-generators and other similar rotating machinery for damage detection purposes. Based on a simplified second-order model of a journal bearing in the state-space, the method employs only the usually monitored vibrations, the shaft radial relative, and the bearing radial absolute vibrations originated by the hydro-generator residual unbalance or by hydraulic excitations in the turbine rotor. This article shows that the method was successfully tested using the shaft and bearing vibration signals synthesized by a mathematical model of a 700 MW hydro-generator, even when these signals are contaminated with random noise. This article also shows the method’s performance when applied to real vibration signals acquired from the modeled hydro-generator. Finally, it discusses the possible measures to improve the method’s efficiency.
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Majumder, Gargi, and Rajiv Tiwari. "Transverse Vibration of Geared-Rotor Integrated With Active Magnetic Bearings in Identification of Multiple Faults." Journal of Dynamic Systems, Measurement, and Control 143, no. 9 (April 15, 2021). http://dx.doi.org/10.1115/1.4050506.
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Abstract This paper presents a novel concept of the modeling, active control of transverse vibration responses, and identification of fault parameters in a geared-rotor system integrated with active magnetic bearings (AMBs). The sources of error in gears while in the operation are the gear mesh deformation, transmission error, and runout, resulting in dynamic forces, excessive vibration, and noise. To avoid any undesirable effect on the gear-pair and other supporting structures, it is essential to investigate these forced vibrations in time and frequency domain. Hence, an approach to monitor and control the transverse vibration of mating gears is presented with the help of AMBs. The AMBs are capable of suppressing the vibration of the system (transients as well as steady-state) by controlled electromagnetic forces considering the rotor vibrational displacement with a closed-loop feedback system. A mathematical model has been developed with geared rotor faults, like the mesh deformation, gear run-out, and asymmetric transmission error. The transmission error has been modeled as the sum of mean and varying components of error in two orthogonal transverse directions. Based on the mathematical model, an identification algorithm has been developed. Considering full spectrum analysis of the rotor vibration and AMB current information, estimation of system parameters, i.e., the equivalent mesh stiffness, mesh damping, gear runouts, the mean and varying transmission error magnitude and phase angles, and the current and displacement constants of AMBs has been performed. Gaussian noise in responses and modeling errors in mathematical models have been added to test the robustness of the proposed algorithm to comply with the experimental settings.
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Unal, Muhammet, Yusuf Sahin, Mustafa Onat, Mustafa Demetgul, and Haluk Kucuk. "Fault Diagnosis of Rolling Bearings Using Data Mining Techniques and Boosting." Journal of Dynamic Systems, Measurement, and Control 139, no. 2 (November 8, 2016). http://dx.doi.org/10.1115/1.4034604.
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Rolling bearings are key components in most mechanical facilities; hence, the diagnosis of their faults is very important in predictive maintenance. Up to date, vibration analysis has been widely used for fault diagnosis in practice. However, acoustic analysis is still a novel approach. In this study, acoustic analysis with classification is used for fault diagnosis of rolling bearings. First, Hilbert transform (HT) and power spectral density (PSD) are used to extract features from the original sound signal. Then, decision tree algorithm C5.0, support vector machines (SVMs) and the ensemble method boosting are used to build models to classify the instances for three different classification tasks. Performances of the classifiers are compared w.r.t. accuracy and receiver operating characteristic (ROC) curves. Although C5.0 and SVM show comparable performances, C5.0 with boosting classifier indicates the highest performance and perfectly discriminates normal instances from the faulty ones in each task. The defect sizes to create faults used in this study are notably small compared to previous studies. Moreover, fault diagnosis is done for rolling bearings operating at different loading conditions and speeds. Furthermore, one of the classification tasks incorporates diagnosis of five states including four different faults. Thus, these models, due to their high performance in classifying multiple defect scenarios having different loading conditions and speeds, can be readily implemented and applied to real-life situations to detect and classify even incipient faults of rolling bearings of any rotating machinery.