Relevant bibliographies by topics / Hydraulic machinery Vibration Data processing

Academic literature on the topic 'Hydraulic machinery Vibration Data processing'

Author: Grafiati
Published: 10 December 2022
Last updated: 29 January 2023

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Journal articles on the topic "Hydraulic machinery Vibration Data processing"

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Tang, Shengnan, Shouqi Yuan, Yong Zhu, and Guangpeng Li. "An Integrated Deep Learning Method towards Fault Diagnosis of Hydraulic Axial Piston Pump." Sensors 20, no. 22 (November 18, 2020): 6576. http://dx.doi.org/10.3390/s20226576.

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A hydraulic axial piston pump is the essential component of a hydraulic transmission system and plays a key role in modern industry. Considering varying working conditions and the implicity of frequent faults, it is difficult to accurately monitor the machinery faults in the actual operating process by using current fault diagnosis methods. Hence, it is urgent and significant to investigate effective and precise fault diagnosis approaches for pumps. Owing to the advantages of intelligent fault diagnosis methods in big data processing, methods based on deep learning have accomplished admirable performance for fault diagnosis of rotating machinery. The prevailing convolutional neural network (CNN) displays desirable automatic learning ability. Therefore, an integrated intelligent fault diagnosis method is proposed based on CNN and continuous wavelet transform (CWT), combining the feature extraction and classification. Firstly, CWT is used to convert the raw vibration signals into time-frequency representations and achieve the extraction of image features. Secondly, a new framework of deep CNN is established via designing the convolutional layers and sub-sampling layers. The learning process and results are visualized by t-distributed stochastic neighbor embedding (t-SNE). The results of the experiment present a higher classification accuracy compared with other models. It is demonstrated that the proposed approach is effective and stable for fault diagnosis of a hydraulic axial piston pump.
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Zhuang, Jin Song, Yi Jian Huang, and Fu Sen Wu. "AR Bispectrum Characteristics of Block Forming Machine’s Vibration Driven by Hydraulic Exciter." Advanced Materials Research 295-297 (July 2011): 2249–53. http://dx.doi.org/10.4028/www.scientific.net/amr.295-297.2249.

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Block forming machine, as a kind of automatic equipments, can quickly compact blocks. Higher-order spectrum analysis emerges as a new effective method in signal processing, which can describe nonlinear coupling, restrain Gaussian noise and reserve phase components. In the paper, a hydraulic exciter applying to block forming machine will be introduced. Then block forming machine’s random vibration signals during the compacting process would be collected, in order to make use of the sample data to build up a time series autoregressive model and bispectrum of three-order accumulation, to analyze AR bispectrum characteristics of the machine’s vibrate signals under different work conditions.
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Benčat, Ján, Daniel Papán, and Mária Stehlíková. "Dynamic Response of Buildings and Structures due to Microtremor Part 1: Industrial Machines Effects." Advanced Materials Research 969 (June 2014): 125–32. http://dx.doi.org/10.4028/www.scientific.net/amr.969.125.

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In this paper a dynamic characterization and vibration analysis has been used for the detection and identification of the machine processing condition and the effect of the production machinery vibration on building complex structures and production process. For sensitive process machines and structures dynamic response due to production machinery calculation procedures was applied using experimental input data via spectral analysis. The dynamic analysis of the cutting production machinery with extreme vibration level is described, too.
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Liu, Hai Sheng, Jie Zhang, Kai Fu Mi, and Jun Xia Gao. "Simulation on Hydraulic-Mechanical Coupling Vibration of Cold Strip Rolling Mill Vertical System." Advanced Materials Research 694-697 (May 2013): 407–14. http://dx.doi.org/10.4028/www.scientific.net/amr.694-697.407.

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Based on vibration problems of a six roller cold rolling mill, hydraulic-machinery coupling vibration system dynamic model of the 2180mm 4-stand tandem cold rolling mills was built integrated the software of MATLAB and ADAMS and simulated. The simulation result was consistent with that of the field test data revealed by rolling mill vibration. Through the comparison of the vertical systems motion displacement, velocity, acceleration under the different work condition, coupling vibration causes and evolution mechanism was analyzed, that had practical value to further control mill motor behavior.
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Liu, Xin, Baoquan Jin, Hongjuan Zhang, and Xuefeng Bai. "Remote Monitoring System for Machinery-electric-hydraulic Coupling Vibration of Food Processing Rolling Mill Screw-down System." Advance Journal of Food Science and Technology 10, no. 5 (February 15, 2016): 360–64. http://dx.doi.org/10.19026/ajfst.10.2083.

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Yang, Xiao Qiang, Ya Ming Gao, Ying Liu, and Jun Han. "Study on Universal Testing Platform of Engineering Machinery." Applied Mechanics and Materials 33 (October 2010): 544–48. http://dx.doi.org/10.4028/www.scientific.net/amm.33.544.

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Due to the multiple types and complexity of fault diagnosis, the general-purpose testing platform of engineering machinery’s hydraulic system is developed for the maintenance of military equipment. The general function and structure of the testing platform is presented. The hardware system consists of modular circuit, integrates control computer of embedded controller with PXI-interfaced modular instrument, program-controlled device, connector and adapter hardware. And the software program comprises data management module, fault diagnosis module coupled to the data acquisition module, signal processing module, experiment condition control module, database access module, system configuration and self-test as well as help module. Further, the hardware characteristics are showed and the principle of hydraulic testing platform is presented. The universal testing platform offers enormous benefits for fault diagnosis and condition monitoring of military equipment and machinery.
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Zhang, Liaojun, Guojiang Yin, Shuo Wang, and Chaonian Guan. "Study on FSI Analysis Method of a Large Hydropower House and Its Vortex-Induced Vibration Regularities." Advances in Civil Engineering 2020 (October 27, 2020): 1–13. http://dx.doi.org/10.1155/2020/7596080.

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The working principle of a large hydropower station is to guide the high-pressure water flow to impact the turbine to rotate and generate electricity. The high-pressure water flow impacts the turbine blades, which forms complex high-speed eddy currents in the spiral case and the draft tube and causes complicated vortex-induced vibration problems. Traditionally used harmonic response methods and dynamic time-history analysis methods are difficult to reflect this complex fluid-solid dynamic coupling problem. In this paper, the bidirectional fluid-structure interaction (FSI) simulation analysis theory for a large hydropower house is studied, and the analysis methods of geometric simulation, mechanical simulation, and vibration energy transmission path simulation are presented. A large-scale 3D fluid-hydraulic machinery-concrete structure coupled model of a hydropower house is established to study the vortex-induced vibration mechanism and coupled vibration law during transient unit operation. A comparison of the fluid results against the in-site data shows good agreement. Structural responses of vibration displacement, velocity, and acceleration reveal coupled regularity of hydraulic machinery-concrete structure-fluid during blades rotating periods, and it comes to the conclusion that the turbine blade rotation is the main vibration source of the hydropower house. The research results can provide a scientific basis for the design and safe operation of the hydropower house.
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Skryabin, Vladimir A. "Manufacturing Parts for Hydraulic Systems of Agricultural Machinery under Conditions of Ultrasonic Cutting." Engineering Technologies and Systems 30, no. 4 (December 30, 2020): 624–36. http://dx.doi.org/10.15507/2658-4123.030.202004.624-636.

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Introduction. The article deals with the problem of reducing the efforts when processing thin-walled bushings for hydraulic systems of agricultural machines with the ultrasonically activated cutting tool to achieve the specified processing accuracy and surface roughness of parts. Materials and Methods. The article describes the technological standards for ultrasonic cutting. To assess the change in the tangential cutting force, a special device was developed to activate ultrasonically the tool for tangential cutting and corresponding experiments were carried out. Results. An upgrading of a screw-cutting lathe equipped with a special device for ultrasonic cutting of low rigidity thin-walled parts is currently being carried out. The upgraded lathe consists of blocks for processing and measuring experimental research data connected to a personal computer. The upgraded lathe allows evaluating the change in cutting forces under traditional turning and ultrasonic cutting to achieve the specified accuracy and roughness of the part surface during the processing process. Discussion and Сonclusion. Processing low rigidity parts on the modernized equipment has shown that providing the effective conditions of manufacturing thin-walled bushings for agricultural machinery (cutting depth and cutting speed) decreases radial and tangential components of the cutting force that helped to reduce the energy consumption of the cutting process and to stabilize quality of the processing.
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Makowski, Ryszard, and Radoslaw Zimroz. "Parametric Time-Frequency Map and its Processing for Local Damage Detection in Rotating Machinery." Key Engineering Materials 588 (October 2013): 214–22. http://dx.doi.org/10.4028/www.scientific.net/kem.588.214.

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The detection of local damage in rotating machinery (gears, bearings) via vibration signal analysis is one of the most powerful techniques in condition monitoring. However, in some cases, especially in heavy industrial machinery, it is difficult to detect damage because of the poor signal-to-noise ratio of the measured vibration. Therefore it is necessary to use unconventional advanced techniques to enhance the signal. In this paper, a novel approach based on parametric time-frequency analysis and further processing for: i) time-varying spectral content modelling, ii) the identification of informative frequency bands by statistical analysis, iii) local damage detection and iv) cycle identification via cepstral analysis, is presented. The proposed procedure is validated using real vibration data from bearings and gearboxes. It is worth noting that this methodology can be also successfully used in time-varying speed conditions (with limited fluctuation).
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Yao, Wei Hao, and Ke Gang Zhao. "The Measurement and Analysis of Torsional Vibration for Rotating Machinery." Applied Mechanics and Materials 365-366 (August 2013): 750–53. http://dx.doi.org/10.4028/www.scientific.net/amm.365-366.750.

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In this paper, the virtual instrument technology is used in torsional vibration study to create a set of torsional vibration natural frequency detection scheme for rotating machinery which is based on the characteristics of controllable one-way overrunning clutch. Also, a test system that is highly sampling frequency, good accuracy and fast data processing capability is developed. This system consists of high-precision dynamic torque sensor, microprocessor-based high-speed data relay module, IPC-based workbench. Finally, the measured results and the calculated results were compared, and it shows that the measured and the calculated results come very close.
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Books on the topic "Hydraulic machinery Vibration Data processing"

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Kleman, Alan. Interfacing microprocessors in hydraulic systems. New York: M. Dekker, 1989.

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2

ZnO bao mo zhi bei ji qi guang, dian xing neng yan jiu. Shanghai Shi: Shanghai da xue chu ban she, 2010.

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3

Use of CAD/CAM for Fluid Machinery Design and Manufacture. Professional Engineering Publishing, 1988.

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Institution of Mechanical Engineers (Great Britain). Fluid Machinery Committee. and Institution of Mechanical Engineers (Great Britain), eds. Use of CAD/CAM for fluid machinery design and manufacture: Papers presented at a seminar organized by the Fluid Machinery Committee of the Power Industries Division of the Institution of Mechanical Engineers and held at the Institution of Mechanical Engineers on 21 January 1988. London: Published by Mechanical Engineering Publications Limited for the Institution of Mechanical Engineers, 1988.

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Book chapters on the topic "Hydraulic machinery Vibration Data processing"

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Muster, G. L., and D. Muster. "Some requirements for automated data-reduction systems suitable for processing vibration measurements taken on high-speed rotating machinery for the support of operational and maintenance decisions." In Vibration and Wear in High Speed Rotating Machinery, 741–57. Dordrecht: Springer Netherlands, 1990. http://dx.doi.org/10.1007/978-94-009-1914-3_43.

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Maradey Lázaro, Jessica Gissella, and Carlos Borrás Pinilla. "Detection and Classification of Wear Fault in Axial Piston Pumps." In Pattern Recognition Applications in Engineering, 286–316. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-1839-7.ch012.

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Variable displacement axial piston hydraulic pumps (VDAP) are the heart of any hydraulic system and are commonly used in the industrial sector for its high load capacity, efficiency, and good performance in the handling of high pressures and speeds. Due to this configuration, the most common faults are related to the wear and tear of internal components, which decrease the operational performance of the hydraulic system and increase maintenance costs. So, through data acquisition such as signals of pressure and the digital processing of them, it is possible to detect, classify, and identify faults or symptoms in hydraulic machinery. These activities form the basis of a condition-based maintenance (CBM) program. This chapter shows the developed methodology to detect and classify a wear fault of valve plate taking into account six conditions and the facilities providing by wavelet analysis and ANNs.
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Conference papers on the topic "Hydraulic machinery Vibration Data processing"

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Palazzolo, A. B., S. Jagannathan, A. F. Kascak, T. Griffin, J. Giriunas, and G. T. Montague. "Piezoelectric Actuator-Active Vibration Control of the Shaft Line for a Gas Turbine Engine Test Stand." In ASME 1993 International Gas Turbine and Aeroengine Congress and Exposition. American Society of Mechanical Engineers, 1993. http://dx.doi.org/10.1115/93-gt-262.

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The Active Vibration Control (AVC) actuators which are discussed in the literature include piezoelectric, electromagnetic (contacting and non-contacting) and hydraulic. This paper presents results of an application of rotating machinery active vibration control (AVC) utilizing piezoelectric actuators. The paper gives actual test data on an aircraft engine test stand-shaft line, unlike the majority of related papers which are entirely theoretical or provide test results only on small, laboratory rotors. The AVC significantly suppresses vibration through two critical speeds of the shaft line.
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Luo, Huageng, Roengchai Chumai, Nicolas Peton, Brian Howard, and Arun Menon. "Torsional Vibration Detection Using High Sampling Rate and High Resolution Keyphasor Information." In ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/detc2013-12367.

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Torsional vibration excitation in rotating machinery can cause system reliability issues or even catastrophic failures. Torsional vibration detection and monitoring becomes an important step in rotating machinery condition monitoring, especially for those machines driven by a variable frequency drive (VFD), a pulse width modulation motor (PWM), or a synchronous motor (SM), etc. Traditionally, the torsional vibration is detected by a phase demodulation process applied to the signals generated by tooth wheels or optical encoders. This demodulation based method has a few unfavorable issues: the installation of the tooth wheels needs to interrupt the machinery normal operation; the installation of the optical barcode is relatively easier, however, it suffers from short term survivability in harsh industrial environments. The geometric irregularities in the tooth wheel and the end discontinuity in the optical encoder will sometimes introduce overwhelming contaminations from shaft order response and its harmonics. In addition, the Hilbert Transform based phase demodulation technique has inevitable errors caused by the edge effect in FFT and IFFT analyses. Fortunately, in many industrial rotating machinery applications, the torsional vibration resonant frequency is usually low and the Keyphasor® and/or encoder for speed monitoring is readily available. Thus, it is feasible to use existing hardware for torsional vibration detection. In this paper, we present a signal processing approach which used the Keyphasor/encoder data digitized by a high sampling rate and high digitization resolution analog-to-digital (A/D) convertor to evaluate the torsional vibration directly. A wavelet decomposition (WD) based method was used to separate the torsional vibration from the shaft speed, so that the time history of the torsional vibrations can be extracted without significant distortions. The developed approach was then validated through a synchronous motor fan drive and an industrial power generation system. Detailed results are presented and discussed in this paper.
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Tijsseling, Arris S., Qingzhi Hou, Bjørnar Svingen, and Anton Bergant. "Acoustic Resonance Experiments in a Reservoir-Pipeline-Orifice System." In ASME 2013 Pressure Vessels and Piping Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/pvp2013-97534.

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Acoustic resonance in liquid-filled pipe systems is an undesirable phenomenon that cannot always be prevented. It causes noise, vibration, fatigue, instability, and it may lead to damage of hydraulic machinery and pipe supports. If possible, resonance should be anticipated in the design process and be part of the hydraulic-transients analysis. This paper describes acoustic resonance tests carried out at Deltares, Delft, The Netherlands, within the framework of the European Hydralab III programme. The test system is a 49 m long pipeline of 206 mm diameter that is discharging water from a 24 m high reservoir through a 240 mm2 orifice to the open atmosphere. The outflow is partly interrupted by a rotating disc which generates flow disturbances at a fixed frequency in the range 1.5 Hz to 100 Hz. In previous studies [1, 2] a similar system was analysed theoretically. Herein experimental data are presented and interpreted. Steady oscillatory behaviour is inferred from pressures measured at four different positions along the pipeline. Heavy pipe vibration during resonance was observed (visually and audibly) and recorded by a displacement transducer.
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Trevillion, Bill. "Development and Application of Graphics Displays for a Mini-Computer Based Vibration Analysis System." In ASME 1992 International Computers in Engineering Conference and Exposition. American Society of Mechanical Engineers, 1992. http://dx.doi.org/10.1115/cie1992-0065.

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Abstract Radian Corporation has developed extensive data display capabilities to analyze vibration and acoustic data from structures and rotating equipment. The Machinery Interactive Display and Analysis System (MIDAS) displays data collected through the acquisition functions of MIDAS. The graphics capabilities include displaying spectra in three-dimensional waterfall and in X-Y formats. Both types of plots can relate vibrations to time, equipment speed, or process parameters. Using menu-driven parameter selection, data can be displayed in formats that are the most useful for analysis. The system runs on a popular mini-computer, and it can be used with a great variety of graphics terminals, workstations, and printer/plotters. The software was designed and written for interactive display and plotting. Automatic plotting of large data files is facilitated by a batch plotting mode. The user can define display formats for the analysis of noise and vibration problems in the electric utility, chemical processing, paper, and automotive industries. This paper describes the history and development of graphics capabilities of the MIDAS system. The system, as illustrated in the examples, has proven efficient and economical for displaying large quantities of data.
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Watson, Matt, Jeremy Sheldon, Sanket Amin, Hyungdae Lee, Carl Byington, and Michael Begin. "A Comprehensive High Frequency Vibration Monitoring System for Incipient Fault Detection and Isolation of Gears, Bearings and Shafts/Couplings in Turbine Engines and Accessories." In ASME Turbo Expo 2007: Power for Land, Sea, and Air. ASMEDC, 2007. http://dx.doi.org/10.1115/gt2007-27660.

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The authors have developed a comprehensive, high frequency (1–100 kHz) vibration monitoring system for incipient fault detection of critical rotating components within engines, drive trains, and generators. The high frequency system collects and analyzes vibration data to estimate the current condition of rotary components; detects and isolates anomalous behavior to a particular bearing, gear, shaft or coupling; and assesses the severity of the fault in the isolated faulty component. The system uses either single/multiple accelerometers, mounted on externally accessible locations, or non-contact vibration monitoring sensors to collect data. While there are published instances of vibration monitoring algorithms for bearing or gear fault detection, there are no comprehensive techniques that provide incipient fault detection and isolation in complex machinery with multiple rotary and drive train components. The author’s techniques provide an algorithm-driven system that fulfills this need. The concept at the core of high frequency vibration monitoring for incipient fault detection is the ability of high frequency regions of the signal to transmit information related to component failures during the fault inception stage. Unlike high frequency regions, the lower frequency regions of vibration data have a high machinery noise floor that often masks the incipient fault signature. The low frequency signal reacts to the fault only when fault levels are high enough for the signal to rise over the machinery noise floor. The developed vibration monitoring system therefore utilizes high frequency vibration data to provide a quantitative assessment of the current health of each component. The system sequentially ascertains sensor validity, extracts multiple statistical, time, and frequency domain features from broadband data, fuses these features, and acts upon this information to isolate faults in a particular gear, bearing, or shaft. The techniques are based on concepts like mechanical transmissibility of structures and sensors, statistical signal processing, demodulation, time synchronous averaging, artificial intelligence, failure modes, and faulty vs. healthy vibration behavior for rotating components. The system exploits common aspects of vibration monitoring algorithms, as applicable to all of the monitored components, to reduce algorithm complexity and computational cost. To isolate anomalous behavior to a particular gear, bearing, shaft, or coupling, the system uses design information and knowledge of the degradation process in these components. This system can function with Commercial Off-The-Shelf (COTS) data acquisition and processing systems or can be adapted to aircraft on-board hardware. The authors have successfully tested this system on a wide variety of test stands and aircraft engine test cells through seeded fault and fault progression tests, as described herein. Verification and Validation (V&V) of the algorithms is also addressed.
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Åman, Rafael, Heikki Handroos, Hannu Kärkkäinen, Jari Jussila, and Pasi Korkealaakso. "Novel ICT-Enabled Collaborative Design Processes and Tools for Developing Non-Road Mobile Machinery." In ASME/BATH 2015 Symposium on Fluid Power and Motion Control. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/fpmc2015-9571.

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The improvement of the energy efficiency is an important topic for non-road mobile machinery developers and manufacturers. These machines normally use fluid power transmission in drivelines and working actuators. New energy efficient technologies, e.g. a hybrid power transmission with an energy recovery feature, have been introduced. Currently most of the manufacturers are still using conventional technologies in their product development process. Human operators have an effect on the overall efficiency of the machines. Taking into account the human effects is difficult and expensive using the conventional design processes and tools. The objective of this study is to provide international machine manufacturers instrumental, yet novel, community and simulation-based (ICT-enabled) tools/methods for the strategic and cost effective development of their product practices and design processes. The development of models and methods will allow for rapid real-time virtual prototyping of complex machines and machine fleets that operate within a number of worksites or geographical conditions. The introduction of this state-of-the art (and going beyond) advancement in real-time virtual technology, simulation, internet based design technologies and software, cyber-physical and big data processing systems, will present a holistic approach to improve the entire product life. Targeted user groups are manufacturers of non-road mobile machinery (i.e. excavators, wheel loaders, etc.). These machines and production systems share the following key features: 1) They are complex mechatronic systems with several interconnections between hydraulic drives; mechanics, electronics, software and 2) they include autonomous, semiautonomous and human driven operated systems. Methods developed will enable machine manufacturers’ access to technologies that will lead to a more cost effective consumer ordinated, life cycle optimization process. This paper will introduce the method of developing customized products in a fast, agile and networked way that will lead to significantly reduced life-cycle costs.
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LIS, ANTONI, MICAH SWEENEY, MAREK SAMOTYJ, and ARTUR ARTUR HANC. "POPULATION BASED PUMPS MONITORING AND BENCHMARKING USING IOT AND EDGE ML LEARNING METHODS." In Structural Health Monitoring 2021. Destech Publications, Inc., 2022. http://dx.doi.org/10.12783/shm2021/36283.

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Machinery monitoring is typically applied to a single machine based on sensor integration and data analysis. Such an approach to a set of machines operating in similar conditions allows for a multivariate analysis for condition monitoring based on a single machine as well as based on group analysis. This paper describes an Industrial Internet-of-Thing (IIoT) concept for condition monitoring of machinery population based on water pumps. The first part provides an introduction to unsupervised anomaly detection based on population modeling with using features calculated from the: mechanical (based on vibration sensors), electrical (voltage and current signals collected from electric motors that drive monitored pumps) and operational processes (such as pressures, flows) signals. Finally, the preliminary results from laboratory testing and demonstration at a wastewater processing plant are presented.
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Rathna Prasad, Sagi, and A. S. Sekhar. "Diagnostics of Fatigue Crack in the Shaft Using Spectral Kurtosis." In ASME Turbo Expo 2019: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/gt2019-90373.

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Abstract Rotating machinery components like shafts subjected to continuous fluctuating loads are prone to fatigue cracks. Fatigue cracks are severe threat to the integrity of rotating machinery. Therefore it is indispensable for early diagnostics of fatigue cracks in shaft to avoid catastrophic failures. From the literature, it is evident that the spectral kurtosis (SK) and fast kurtogram were used to detect the faults in bearings and gears. The present study illustrates the use of SK and fast kurtogram for early fatigue crack detection in the shaft using vibration data. To perform this study, experiments are conducted on a rotor test rig which is designed and developed according to the function specification proposed by ASTM E468-11 standard. Fatigue crack is developed, on three shaft specimens, each seeded with the same circumferential V-Notch configuration, by continuous application of stochastic loads on the shaft using electrodynamic shaker in addition to the unbalance forces that arise in normal operating conditions. Vibration data is acquired from various locations of the rotor, using different sensors like miniature accelerometers, laser vibrometer and wireless telemetry strain gauge, till the shaft specimen develops fatigue crack. The analysis results show that the combination of SK and fast kurtogram is an effective signal processing technique for detecting the fatigue crack in the shaft.
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Mauricio, Alexandre, Shuangwen Sheng, and Konstantinos Gryllias. "Condition Monitoring of Wind Turbine Planetary Gearboxes Under Different Operating Conditions." In ASME Turbo Expo 2019: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/gt2019-91136.

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Abstract Digitally enhanced services for wind power could reduce Operations and Maintenance (O&M) costs as well as the Levelised Cost Of Energy (LCOE). Therefore, there is a continuous need for advanced monitoring techniques which can exploit the opportunities of Internet of Things (IoT) and Big Data Analytics, revolutionizing the future of the energy sector. The heart of wind turbines is a rather complex epicyclic gearbox. Among others, extremely critical gearbox components which are often responsible for machinery stops are the rolling element bearings. The vibration signatures of bearings are rather weak compared to other components, such as gears, and as a result an extended number of signal processing techniques and tools have been proposed during the last decades, focusing towards accurate, early, and on time bearing fault detection with limited false alarms and missed detections. Envelope Analysis is one of the most important methodologies, where an envelope of the vibration signal is estimated usually after filtering around a frequency band excited by impacts due to the bearing faults. Different tools, such as Kurtogram, have been proposed in order to accurately select the optimum filter parameters (center frequency and bandwidth). Cyclic Spectral Correlation and Cyclic Spectral Coherence, based on Cyclostationary Analysis, have been proved as very powerful tools for condition monitoring. The monitoring techniques seem to have reached a mature level in case a machinery operates under steady speed and load. On the other hand, in case the operating conditions change, it is still unclear whether the change of the monitoring indicators is due to the change of the health of the machinery or due to the change of the operating parameters. Recently, the authors have proposed a new tool called IESFOgram, which is based on Cyclic Spectral Coherence and can automatically select the filtering band. Furthermore, the Cyclic Spectral Coherence is integrated along the selected frequency band leading to an Improved Envelope Spectrum. In this paper, the performance of the tool is evaluated and further extended on cases operating under different speeds and different loads. The effectiveness of the methodology is tested and validated on the National Renewable Energy Laboratory (NREL) wind turbine gearbox vibration condition monitoring benchmarking data set which includes various faults with different levels of diagnostic complexity as well as various speed and load operating conditions.
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Tzeng, George T. "Encoder-Less Synchronized Averaging Using Order Tracking and Interpolation." In ASME 2004 International Mechanical Engineering Congress and Exposition. ASMEDC, 2004. http://dx.doi.org/10.1115/imece2004-61148.

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Synchronized averaging is a very useful signal processing technique, in particular, for condition monitoring of rotating machinery. It enhances the signal to noise ratio by attenuating noises that are not repeated from one rotation to the next. Its use, however, is limited due to the costly hardware needed to trigger the sampling at exactly the same angular positions rotation after rotation. This paper describes an improved order tracking technique which employs a Kalman filter to track the instantaneous rotating speed of machinery and an interpolation technique to resample data obtained under constant sampling time interval into data sampled at constant angular increments. Experiments were conducted to validate the proposed algorithm. Comparing the synchronized average obtained by the order tracking algorithm with the true average using encoder triggering, no significant difference can be seen until 3x of meshing frequency. Since the technique only requires band-pass filtered vibration and a once-per-revolution index signal, it is much simpler compared to the existing technique which requires complex and cumbersome hardware to track the rotating speed.
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