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Relevant bibliographies by topics / Simulation of fault signals

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Academic literature on the topic 'Simulation of fault signals'

Author: Grafiati

Published: 28 June 2021

Last updated: 1 February 2022

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Journal articles on the topic "Simulation of fault signals"

1

Liu, Xiaoyang, Haizhou Huang, and Jiawei Xiang. "A Personalized Diagnosis Method to Detect Faults in a Bearing Based on Acceleration Sensors and an FEM Simulation Driving Support Vector Machine." Sensors 20, no. 2 (January 11, 2020): 420. http://dx.doi.org/10.3390/s20020420.

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Classification of faults in mechanical components using machine learning is a hot topic in the field of science and engineering. Generally, every real-world running mechanical system exhibits personalized vibration behaviors that can be measured with acceleration sensors. However, faulty samples of such systems are difficult to obtain. Therefore, machine learning methods, such as support vector machine (SVM), neural network (NNs), etc., fail to obtain agreeable fault detection results through smart sensors. A personalized diagnosis fault method is proposed to activate the smart sensor networks using finite element method (FEM) simulations. The method includes three steps. Firstly, the cosine similarity updated FEM models with faults are constructed to obtain simulation signals (fault samples). Secondly, every simulation signal is separated into sub-signals to solve the time-domain indexes to generate the faulty training samples. Finally, the measured signals of unknown samples (testing samples) are inserted into the trained SVM to classify faults. The personalized diagnosis method is applied to detect bearing faults of a public bearing dataset. The classification accuracy ratios of six types of faults are 90% and 92.5%, 87.5% and 87.5%, 85%, and 82.5%, respectively. It confirms that the present personalized diagnosis method is effectiveness to detect faults in the absence of fault samples.

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Huo, Linsheng, Gangbing Song, Satish Nagarajaiah, and Hongnan Li. "Semi-active vibration suppression of a space truss structure using a fault tolerant controller." Journal of Vibration and Control 18, no. 10 (October 7, 2011): 1436–53. http://dx.doi.org/10.1177/1077546311421514.

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In recent years, magneto-rheological (MR) dampers have been used to control the response of structures. This paper presents the design and application of an H∞ fault detection and isolation (FDI) filter and fault tolerant controller (FTC) for truss vibration control systems using MR dampers. A linear matrix inequality formulation is used to design a full order robust H∞ filter to estimate faulty input signals. A fault tolerant H∞ controller is designed for the combined system of plant and filter, minimizing the control objective selected in the presence of disturbances and faults. A truss structure with an MR damper is used to validate the FDI and FTC controller design through numerical simulations. The residuals obtained from the filter through simulation clearly identify the fault signals. The simulation results of the proposed FTC controller confirm its effectiveness for vibration suppression of the faulty truss system.

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Zhang, Changfan, Huijun Liao, Xiangfei Li, Jian Sun, and Jing He. "Fault Reconstruction Based on Sliding Mode Observer for Current Sensors of PMSM." Journal of Sensors 2016 (2016): 1–9. http://dx.doi.org/10.1155/2016/9307560.

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This paper deals with a method of phase current sensor fault reconstruction for permanent magnet synchronous motor (PMSM) drives. A new state variable is introduced so that an augmented system can be constructed to treat PMSM sensor faults as actuator faults. This method uses the PMSM two-phase stationary reference frame fault model and a sliding mode variable structure observer to reconstruct fault signals. A logic algorithm is built to isolate and identify the faulty sensor for a stator phase current fault after reconstructing the two-phase stationary reference frame fault signals, which allows the phase fault signals to be reconstructed. Simulation results are presented to illustrate the functionality of the theoretical developments.

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Fei, Cheng-Wei, Yat-Sze Choy, Guang-Chen Bai, and Wen-Zhong Tang. "Multi-feature entropy distance approach with vibration and acoustic emission signals for process feature recognition of rolling element bearing faults." Structural Health Monitoring 17, no. 2 (January 24, 2017): 156–68. http://dx.doi.org/10.1177/1475921716687167.

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To accurately reveal rolling bearing operating status, multi-feature entropy distance method was proposed for the process character analysis and diagnosis of rolling bearing faults by the integration of four information entropies in time domain, frequency domain and time–frequency domain and two kinds of signals including vibration signals and acoustic emission signals. The multi-feature entropy distance method was investigated and the basic thought of rolling bearing fault diagnosis with multi-feature entropy distance method was given. Through rotor simulation test rig, the vibration and acoustic emission signals of six rolling bearing faults (ball fault, inner race fault, outer race fault, inner ball faults, inner–outer faults and normal) are gained under different rotational speeds. In the view of the multi-feature entropy distance method, the process diagnosis of rolling bearing faults was implemented. The analytical results show that multi-feature entropy distance fully reflects the process feature of rolling bearing faults with the change of rotating speed; the multi-feature entropy distance with vibration and acoustic emission signals better reports signal features than single type of signal (vibration or acoustic emission signal) in rolling bearing fault diagnosis; the proposed multi-feature entropy distance method holds high diagnostic precision and strong robustness (anti-noise capacity). This study provides a novel and useful methodology for the process feature extraction and fault diagnosis of rolling element bearings and other rotating machinery.

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Dou, Chun Hong. "Fault Feature Extraction for Gearboxes Using Empirical Mode Decomposition." Advanced Materials Research 383-390 (November 2011): 1376–80. http://dx.doi.org/10.4028/www.scientific.net/amr.383-390.1376.

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The paper uses empirical mode decomposition to extract the fault feature of gearboxes. Traditional techniques fail to process the non-stationary and nonlinear signals. Empirical mode decomposition is a powerful tool for the non-stationary and nonlinear signal analysis and has attracted considerable attention recently. First, a simulation signal is used to measure the performance of the empirical mode decomposition method. Then, the empirical mode decomposition method is applied to analyze the signals captured from the gearbox with multiple faults and successfully extracts the multiple fault information from the collected signals. The results show that empirical mode decomposition could be a helpful method for mechanical fault feature extraction.

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Liu, Shu Lin, You Fu Tang, Ji Cheng Liu, and Ying Hui Liu. "Research of Fault Feature Extraction Based on High Order Cyclic Statistics for Reciprocating Compressor Gas Valves." Applied Mechanics and Materials 44-47 (December 2010): 2094–98. http://dx.doi.org/10.4028/www.scientific.net/amm.44-47.2094.

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. This paper proposes an approach of fault feature extraction for reciprocating compressor gas valves based on theory of cyclic statistics. First, the strength and weakness of the third-order cyclic statistics in extracting signal features are investigated by simulation signals. Since vibration signals for reciprocating compressor gas valves are of typical cyclic stationary, a new method of fault feature extraction is then proposed based on the simulation results. The method utilizes the cyclic bi-spectrum to extract fault features for the corresponding frequencies. The results show that the cyclic bi-spectrum characteristics for typical faults of gas valves are apparently different, and that the typical faults of reciprocating compressor gas valves can be diagnosed exactly. So the new method proposed in this paper is effective and feasible.

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Kang, Wei, Guang Jian Chang, and Xin Yong Qiao. "Approach to Diagnose Gear Tooth-Broken Fault Based on Web." Advanced Materials Research 433-440 (January 2012): 2257–62. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.2257.

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Gear box is one of the most important parts of vehicle transmission. Its fault influences the mobility of vehicle. In all the gear faults tooth-broken have the most serious harm. In this paper fault simulation test was taken on armored vehicle, and the vibration signals of gear box were measured. A signal analysis and fault diagnosis system was developed based on wireless web to analyze the signals in time domain and frequency domain. In this way a type of remote diagnosis is realized to diagnosing gear fault.

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Zhang, Dingcheng, Dejie Yu, and Xing Li. "Optimal resonance-based signal sparse decomposition and its application to fault diagnosis of rotating machinery." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 231, no. 24 (November 26, 2016): 4670–83. http://dx.doi.org/10.1177/0954406216671542.

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The fault diagnosis of rotating machinery is quite important for the security and reliability of the overall mechanical equipment. As the main components in rotating machinery, the gear and the bearing are the most vulnerable to faults. In actual working conditions, there are two common types of faults in rotating machinery: the single fault and the compound fault. However, both of them are difficult to detect in the incipient stage because the weak fault characteristic signals are usually submerged by strong background noise, thus increasing the difficulty of the weak fault feature extraction. In this paper, a novel decomposition method, optimal resonance-based signal spares decomposition, is applied for the detection of those two types of faults in the rotating machinery. This method is based on the resonance-based signal spares decomposition, which can nonlinearly decompose vibration signals of rotating machinery into the high and the low resonance components. To extract the weak fault characteristic signals in the presence of strong noise effectively, the genetic algorithm is used to obtain the optimal decomposition parameters. Then, the optimal high and low resonance components, which include the fault characteristic signals of rotating machinery, can be obtained by using the resonance-based signal spares decomposition method with the optimal decomposition parameters. Finally, the high and the low resonance components are subject to the Hilbert transform demodulation analysis; the faults of rotating machinery can be diagnosed based on the obtained envelop spectra. The optimal resonance-based signal spares decomposition method is successfully applied to the analysis of the simulation and experiment vibration signals. The analysis results demonstrate that the proposed method can successfully extract the fault features in rotating machinery.

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Papathanasopoulos, Dimitrios A., Konstantinos N. Giannousakis, Evangelos S. Dermatas, and Epaminondas D. Mitronikas. "Vibration Monitoring for Position Sensor Fault Diagnosis in Brushless DC Motor Drives." Energies 14, no. 8 (April 16, 2021): 2248. http://dx.doi.org/10.3390/en14082248.

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A non-invasive technique for condition monitoring of brushless DC motor drives is proposed in this study for Hall-effect position sensor fault diagnosis. Position sensor faults affect rotor position feedback, resulting in faulty transitions, which in turn cause current fluctuations and mechanical oscillations, derating system performance and threatening life expectancy. The main concept of the proposed technique is to detect the faults using vibration signals, acquired by low-cost piezoelectric sensors. With this aim, the frequency spectrum of the piezoelectric sensor output signal is analyzed both under the healthy and faulty operating conditions to highlight the fault signature. Therefore, the second harmonic component of the vibration signal spectrum is evaluated as a reliable signature for the detection of misalignment faults, while the fourth harmonic component is investigated for the position sensor breakdown fault, considering both single and double sensor faults. As the fault signature is localized at these harmonic components, the Goertzel algorithm is promoted as an efficient tool for the harmonic analysis in a narrow frequency band. Simulation results of the system operation, under healthy and faulty conditions, are presented along with the experimental results, verifying the proposed technique performance in detecting the position sensor faults in a non-invasive manner.

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Zeng, Wen Feng, Yu Min Tian, Bao Hui Zhu, and Dong Li. "The Design of a Maintenance Simulation System for Lasers." Advanced Materials Research 926-930 (May 2014): 1440–43. http://dx.doi.org/10.4028/www.scientific.net/amr.926-930.1440.

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The MCU system is used to simulate laser signals and the signals received by avalanche transistors so as to conduct signal detection of actual circuit boards.With establishing a library of fault cases through the computer serial port, the MCU and the fault setting module can be based on to realize the fault simulation of actual circuit boards and conduct the training in fault detection and removal. The designed fault setting software and assessment software can be combined to assess the training effects of fault analysis, detection and removal. The developed prototype passes the test of training, showing good results and high training benefits

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Dissertations / Theses on the topic "Simulation of fault signals"

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Hou, Junwei. "Concurrent fault simulation for mixed-signal circuits." Diss., Georgia Institute of Technology, 2001. http://hdl.handle.net/1853/15735.

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Wang, Xiaofeng. "Simulation models for rolling bearing vibration generation and fault detection via neural networks." Thesis, University of Oxford, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.362159.

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Gomes, Alfred Vincent. "Alternate Test Generation for Detection of Parametric Faults." Diss., Georgia Institute of Technology, 2003. http://hdl.handle.net/1853/5285.

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Tests for detecting faults in analog and mixed-signal circuits have been traditionally derived from the datasheet speci and #64257;cations. Although these speci and #64257;cations describe important aspects of the device, in many cases these application oriented tests are costly to implement and are inefficient in determining product quality. Increasingly, the gap between speci and #64257;cation test requirements and the capabilities of test equipment has been widening. In this work, a systematic method to generate and evaluate alternate tests for detecting parametric faults is proposed. We recognize that certain aspects of analog test generation problem are not amenable to automation. Additionally, functional features of analog circuits are widely varied and cannot be assumed by the test generator. To overcome these problems, an extended device under test (DUT) model is developed that encapsulates the DUT and the DUT speci and #64257;c tasks. The interface of this model provides a well de and #64257;ned and uniform view of a large class of devices. This permits several simpli and #64257;cations in the test generator. The test generator is uses a search-based procedure that requires evaluation of a large number of candidate tests. Test evaluation is expensive because of complex fault models and slow fault simulation techniques. A tester-resident test evaluation technique is developed to address this issue. This method is not limited by simulation complexity nor does it require an explicit fault model. Making use of these two developments, an efficient and automated test generation method is developed. Theoretical development and a number of examples are used to illustrate various concepts that are presented in this thesis.

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Davari, Far Mehrdad. "Contribution to the fault diagnosis in photovoltaic systems." Amiens, 2014. http://www.theses.fr/2014AMIE0117.

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L'objectif de cette thèse était de développer des méthodes de détection de défauts dans les installations photovoltaïques. Une approche basée modèle et fondée sur la simulation pour détecter les défauts dans le système photovoltaïque résidentiel (RPS) est proposée. Un modèle hybride simplifié de panneau photovoltaïque utilisé avec un environnement MATLAB est développé et validé dans cette thèse. Son originalité c'est qu'il tourne en temps réel et il est suffisamment flexible pour simuler des systèmes photovoltaïques solaires avec des échelles différentes, avec ou sans diodes de dérivation et de diverses technologies. Ensuite, une nouvelle technique de détection de défaut a été introduite. Elle se compose de deux parties principales. Une partie passive, qui permettra de détecter une défaillance en comparant les signaux mesurés et ceux obtenus par le modèle. La partie active consiste à analyser les différents attributs pour localiser et définir le type de défaut. Enfin, les résultats obtenus par simulation ou en pratique de la méthode et les techniques proposées sont satisfaisantes et ouvrent plus de perspectives dans ce domaine
The aim of this thesis was to develop methods for detecting faults in photovoltaic installations. An approach based on model and simulation to detect defects in the residential photovoltaic System (RPS) is proposed. A simplified hybridphotovoltaic panel used with MATLAB environment is developed and validated in this thesis. Its originality is that it runs in real time and it is flexible enough to simulate solar photovoltaic Systems with different scales, with or without bypass diodes and various technologies. Then a new technique for fault détection has been introduced. It consists of two main parts. A passive part, which will detect a fault by comparing the measured signals, and those obtained by the model. The active part is to analyze the different attributes to locale and identify the type of fault. Finally, the results obtained by simulation or practice of the method and the proposed techniques are satisfactory and open more perspectives in this area

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Martínek, Marek. "Tvorba SW pro generování signálu simulující závady rotačních systémů." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2021. http://www.nusl.cz/ntk/nusl-442837.

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This diploma thesis deals with the design and creation of an algorithm for generating simulated signal data from a vibration diagnostics device. The first part is focused on theoretical acquaintance with vibration diagnostics and characteristics of individual defects of rotary machines. The next part deals with the possibilities of mathematical and kinematic simulations using a computer software. The main part of this work is dedicated to design and creation of software for generating simulated signal data. In the last part, the principle of simulation of specific defects of rotary machines is clearly demonstrated.

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Bhojwani, Soniya Naresh. "Simulation of Physiological Signals using Wavelets." University of Akron / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=akron1193079604.

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Smith, Jason. "A Sensor Fault Detection Simulation Tool." Miami University / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=miami1193282225.

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Warshawsky, Avrum S. "Distributed fault simulation using vector set partitioning." Thesis, McGill University, 1991. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=59903.

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To explore the potential speedup to be obtained through parallelism, a mathematical model for the performance of fault simulation is developed.
A framework for performing fault simulation in a distributed environment is developed based on the assumption that fault simulation of different vectors can be run independently on different processors. This can be done using any uniprocessor fault simulator and requires only a fairly simple and low bandwidth communication mechanism. This communication mechanism distributes the list of faults detected by each simulator to all other simulators so that the simulation can be controlled based on global criteria such as the fault coverage obtained by the distributed simulator, and the amount of work to be done by each processor is dynamically reduced through fault dropping and fault-free dropping based on the coverage obtained by all processors.
Finally, a distributed simulator is implemented using the above mechanism on a network of workstations using the uniprocessor fault simulator Tulip.

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Kwong, Albert L. C. "Parallel fault simulation on the C.RAM architecture." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/tape17/PQDD_0001/MQ34387.pdf.

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Wang, Xiaolin. "Synchronous fault simulation by surrogate with exceptions." Diss., The University of Arizona, 1989. http://hdl.handle.net/10150/184687.

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The contribution of this dissertation is the development of a completely new and accurate algorithm SFSSE for synchronous fault simulation of sequential circuits. The distinctive difference between SFSSE (Synchronous Fault Simulation by Surrogate with Exceptions) and similar approaches for fault simulation in combinational logic circuits is that SFSSE is capable of handling faults stored in more than one memory elements and the reconvergence over time of the stored fault effect with the original fault. The experimental result shows a significant improvement for SFSSE by comparing its execution time to that of parallel fault simulation. After a stored fault list is established during one clock period, all paths from the output of that memory element to the primary outputs might be blocked in subsequent clock periods. A fault is usually propagated through many paths in various subnetworks over several clock periods, and it is detected when only one of these paths reaches a primary output. A new idea for efficiency is suggested in the last chapter to avoid the unproductive simulation activity. In that approach the waste of simulation time is avoided by overlapping the simulation of multiple clock periods.

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Books on the topic "Simulation of fault signals"

1

Gardner, Floyd Martin. Simulation techniques: Models of communication signals and processes. New York: Wiley, 1997.

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Kehil, D. Passive sonar signals simulation using frequency domain techniques. Birmingham: University of Birmingham, 1988.

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Knight, J. C. Second generation experiments in fault tolerant software. Charlottesville, Va: Dept. of Computer Science, School of Engineering and Applied Science, University of Virginia, 1987.

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4

Sammis, Charles G., and Yehuda Ben-Zion. Mechanics, structure and evolution of fault zones. Basel: Birkhauser, 2010.

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Philippe, Müllhaupt, and SpringerLink (Online service), eds. Advances in the Theory of Control, Signals and Systems with Physical Modeling. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2011.

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6

Litt, John. Sensor fault detection and diagnosis simulation of a helicopter engine in an intelligent control framework. [Washington, DC]: National Aeronautics and Space Administration, 1994.

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Kuipers, Benjamin. Self-calibrating models for dynamic monitoring and diagnosis: Final report covering the period 1 February 1992 to 31 March 1995. Austin, Tex: University of Texas at Austin, 1996.

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Bedrosian, Edward. Concept-level analytical procedures for loading nonprocessing communication satellites with nonantijam signals. Santa Monica, CA: Rand, 1996.

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Institution of Engineering and Technology. Thermal Power Plant Simulation and Control. Stevenage: IET, 2003.

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Rogers, A. M. Monte Carlo simulation of peak-acceleration attenuation using a finite-fault uniform-patch model: A parameter study. [Denver, CO]: Dept. of the Interior, U.S. Geological Survey, 1995.

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Book chapters on the topic "Simulation of fault signals"

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Huber, John P., and Mark W. Rosneck. "Fault Simulation." In Successful ASIC Design the First Time Through, 129–43. Boston, MA: Springer US, 1991. http://dx.doi.org/10.1007/978-1-4684-7885-3_7.

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Ulrich, Ernst G., Vishwani D. Agrawal, and Jack H. Arabian. "Concurrent Fault Simulation." In Concurrent and Comparative Discrete Event Simulation, 57–62. Boston, MA: Springer US, 1994. http://dx.doi.org/10.1007/978-1-4615-2738-1_4.

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Santucci, Jean-François, Paul Bisgambiglia, and Dominique Federici. "Behavioral Fault Simulation." In Advanced Techniques for Embedded Systems Design and Test, 261–84. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4757-4419-4_11.

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Krstić, Angela, and Kwang-Ting Cheng. "Delay Fault Simulation." In Frontiers in Electronic Testing, 77–100. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4615-5597-1_6.

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Walker, Duncan Moore Henry. "Fault Analysis." In Yield Simulation for Integrated Circuits, 51–85. Boston, MA: Springer US, 1987. http://dx.doi.org/10.1007/978-1-4757-1931-4_5.

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Khare, Jitendra B., and Wojciech Maly. "Contamination-Defect-Fault (CDF) Simulation." In From Contamination to Defects, Faults and Yield Loss, 37–46. Boston, MA: Springer US, 1996. http://dx.doi.org/10.1007/978-1-4613-1377-9_3.

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Navabi, Zainalabedin. "Fault Simulation Applications and Methods." In Digital System Test and Testable Design, 103–42. Boston, MA: Springer US, 2010. http://dx.doi.org/10.1007/978-1-4419-7548-5_4.

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Ulrich, Ernst G., Vishwani D. Agrawal, and Jack H. Arabian. "Fault Simulation of Diagnostic Programs." In Concurrent and Comparative Discrete Event Simulation, 95–108. Boston, MA: Springer US, 1994. http://dx.doi.org/10.1007/978-1-4615-2738-1_8.

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Azambuja, José Rodrigo, Fernanda Kastensmidt, and Jürgen Becker. "Simulation Fault Injection Experimental Results." In Hybrid Fault Tolerance Techniques to Detect Transient Faults in Embedded Processors, 63–68. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-06340-9_5.

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Chibani, Kais, Adrien Facon, Sylvain Guilley, Damien Marion, Yves Mathieu, Laurent Sauvage, Youssef Souissi, and Sofiane Takarabt. "Fault Analysis Assisted by Simulation." In Automated Methods in Cryptographic Fault Analysis, 263–77. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-11333-9_12.

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Conference papers on the topic "Simulation of fault signals"

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Dedoussis, V., K. Mathioudakis, and K. D. Papailiou. "Numerical Simulation of Blade Fault Signatures From Unsteady Wall Pressure Signals." In ASME 1994 International Gas Turbine and Aeroengine Congress and Exposition. American Society of Mechanical Engineers, 1994. http://dx.doi.org/10.1115/94-gt-289.

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A method for establishing signatures of faults in the rotating blades of a gas turbine compressor is presented. The method employs a panel technique for the calculation of the flow field around blade cascades, with disrupted periodicity, a situation which is encountered when a blade fault has occurred. From this calculation, time signals of the pressure at a location on the casing wall, facing the rotating blades, are constituted. Processing these signals, in combination with “healthy” pressure signals allows the constitution of fault signatures. The proposed method employs geometrical data, as well as data about the operating point of the engine. It gives the possibility of establishing the fault signatures without the need of performing experiments with implanted faults. The successful application of the method is demonstrated by comparison of signatures obtained by simulation to signatures derived from experiments with implanted blade faults, in an industrial gas turbine.

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Bartelmus, Walter, and Radosław Zimroz. "Gearbox Systems Dynamic Modelling for Diagnostic Fault Detection." In ASME 2003 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2003. http://dx.doi.org/10.1115/detc2003/ptg-48080.

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The paper deals with mathematical modelling and computer simulation of a gearbox driving system with a double stage gearbox. Mathematical modelling and computer simulations are used for supporting diagnostic inference. Vibration is thought of as a signal of gear condition. It is stressed that vibration generated by gears is influenced by many factors. These factors are divided into four groups: design, production technology, operational, condition change. The condition change of a gearbox is given by gear faults that are divided into single faults such as a tooth crack or breakage or distributed faults as pitting, scuffing, and erosion. The faults are modelled in the case of a crack as a change of tooth stiffness in the case of distributed faults they are given multi-parameter functions. Simulated signals undergo signal analysis by spectrum, cepstrum, time-frequency spectrogram. It has been shown by computer simulation that single and distributed faults are identified by cepstrum. For explicit fault identification time-frequency spectrogram has to be additionally used. The computer simulation results are confirmed by analysis of measured vibration signals received from a gearbox wall/housing. The aim of mathematical modelling and computer simulation, besides finding the relationship between gear condition and vibration signal is in the future to give vibration signals for neural network training.

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Leger, Gildas, and Antonio Gines. "Likelihood-sampling adaptive fault simulation." In 2017 International Mixed Signals Testing Workshop (IMSTW). IEEE, 2017. http://dx.doi.org/10.1109/ims3tw.2017.7995200.

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Korkealaakso, Pasi, Asko Rouvinen, and Aki Mikkola. "Multibody Simulation Formulations in Fault Diagnosis of a Reel." In ASME 2005 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2005. http://dx.doi.org/10.1115/detc2005-84923.

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In order to improve the recognition of faulty situations, the model-based fault diagnosis can be used together with signal processing methods. In this study, faults and abnormalities of a reel is studied by employing the multibody simulation approach. The reel under consideration consists of a number of subsystems including hydraulics, electrical drives and mechanical parts, which are coupled by joints, friction forces and contact forces. Using the multibody simulation approach, the complete model of the reel can be obtained by coupling different subsystems together. Three well-known multibody formulations, a method of Lagrange multipliers, an Augmented Lagrangian method and a method based on projection matrix R, are briefly described and compared in order to find out the most efficient method for simulating the studied reel. It is noteworthy, that the method based on an Augmented Lagrangian formulation is also capable of real-time fault diagnosis of a reel.

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Gangsar, Purushottam, and Rajiv Tiwari. "Analysis of Time, Frequency and Wavelet Based Features of Vibration and Current Signals for Fault Diagnosis of Induction Motors Using SVM." In ASME 2017 Gas Turbine India Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/gtindia2017-4774.

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This paper presents a comparative analysis of the time, frequency and time-frequency domain based features of the vibration and current signals for identifying various faults in induction motors (IMs) using support vector machine (SVM). Four mechanical faults (bearing fault, unbalanced rotor, bowed rotor and misaligned rotor), and three electrical faults (broken rotor bars, stator winding fault with two severity levels and phase unbalance with two severity levels) are considered in the present study. The proposed fault diagnosis consists of three steps. In the first step, the vibration in three orthogonal directions and the current in three phases are acquired from the healthy and faulty motors using a machine fault simulator (MFS). In second step, useful statistical features are extracted from the time, frequency and time-frequency domain (continuous wavelet transform (CWT)) of the signal. For the effective fault diagnosis, SVM parameters are optimally selected based on the grid-search method along with 5-fold cross-validation, and the effective fault features are selected based on the wrapper model. Finally, the fault diagnosis of IM is performed using optimal SVM parameters and effective features as input to the SVM. The classification performance of all methodologies developed in three domains is compared for various operating conditions of IMs. The test results showed that the developed methodology could isolate ten IM fault conditions successfully based on features from all three domains at all IM operating conditions; however, time-frequency features give the best results.

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Yang, J. G., K. Zhao, Y. Pan, and X. D. Liu. "Research on the Simulation Method of Dynamic Response of High Voltage Circuit Breaker During Operation." In ASME 2016 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/imece2016-66357.

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High voltage circuit breaker (CB) is one of the most important components in high voltage circuit. In the process of operation, some kinds of mechanical faults such as jam fault, component deformation and component failure may occur and affect the performance of the circuit breaker. But, generally it is difficult to diagnose these faults. To obtain the characteristics of these faults in the high voltage circuit breaker, in this paper, a simulation method for high voltage circuit breakers is investigated. Firstly, the dynamic models of the operating mechanism of the high voltage circuit breaker are established and the simulations are performed; then the vibration signals at the monitoring points can be obtained based on finite element simulation. Based on these signals, the characteristics of some typical mechanical faults may be researched. The work in this paper is helpful to recognize the failure mechanism of the high voltage circuit breaker and improve the veracity of the fault diagnosis.

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Venkataram, Nithin, Harish K. Bhagavan, Rahul M. Cadambi, and Arun R. Rao. "Numerical Simulation and Experimental Validation of Frequency Based Fault Detection and Localization in a Planetary Gearbox Under Dynamic Condition." In ASME 2019 Gas Turbine India Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/gtindia2019-2523.

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Abstract The planetary gearbox is often susceptible to faults under dynamic condition. Most of the literature assumes that gearboxes are free from defects. But in real-time working condition these assumptions are not accurate. Therefore the challenge lies in identifying and localizing a fault in planetary gearbox under dynamic condition. In this paper, the focus is on modelling and simulation of a fault in a planetary gearbox and validate the same with experimental tests. A planetary gearbox is modelled as per DIN standard and simulated for time and frequency domain signals. On comparing a fault free and fault induced frequency domain signals, a small peaks are observed on either side of the mesh frequencies, indicating the presence of a fault in the planetary gearbox. These peaks around the mesh frequencies are used to localize the fault in a planetary gearbox. Simulation results are validated with the experimental test results of the planetary gearbox under dynamic conditions. Similar trend is observed in simulation and experimental results.

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Parky, Joonsung, Srinadh Madhavapeddiz, Alessandro Paglieri, Chris Barrz, and Jacob A. Abrahamy. "Defect-based analog fault coverage analysis using mixed-mode fault simulation." In 2009 IEEE 15th International Mixed-Signals, Sensors, and Systems Test Workshop (IMS3TW). IEEE, 2009. http://dx.doi.org/10.1109/ims3tw.2009.5158688.

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Hou, Chin-Che, and Min-Chun Pan. "Feature Extraction Based on Teager-Kaiser Energy Operation and Envelope Spectra for Fault Detection of a Reciprocating Compressor." In ASME 2020 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/imece2020-24550.

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Abstract In this paper, signal analysis techniques based on Teager-Kaiser energy operation and envelope spectra for fault detection of the discharge valve of a reciprocating compressor is proposed. The method can accurately identify the existing fault of vibration signal features that it simulated by the synthetic signals. A two-phase study was designed to explore the signals simulation and the experimental validation. Signals simulation, which is based on the operation of a reciprocating compressor, and experiment design, which uses three conditions. The first stage is to simulate the operation of the reciprocating compressor, which is to simulate a synthetic signal for the cycle and impact. The synthetic signal is composed of a noise, square wave, and pulse wave. In this study, the synthetic signal is signal-processed by the Teager-Kaiser energy operator and the envelope spectrum that they can effectively extract feature signal and the noise almost is eliminated. The second stage is applied to the signal processing technique proposed in the first stage. Experimental verification of experiment design by the different operating conditions of reciprocating compressor valves. Through the above analysis technology, it is proved that the synthetic signal can be eliminated the background noise to obtain the feature signal. The feasibility of the proposed approach is verified by simulation results, the experiment is to validate with the measurement signals from a six-cylinder reciprocating compressor under different valve conditions. Simulations and experimental results support the proposed technology positively.

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Wang, Chongyu, Di Zhang, and Yonghui Xie. "Research on Fault Diagnosis of Steam Turbine Rotor Unbalance and Parallel Misalignment Based on Numerical Simulation and Convolutional Neural Network." In ASME Turbo Expo 2021: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/gt2021-60247.

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Abstract The steam turbine rotor is still the main power generation equipment. Affected by the impact of new energy on the power grid, the steam turbine needs to participate in peak load regulation, which will make turbine rotor components more prone to failure. The rotor is an important equipment of a steam turbine. Unbalance and misalignment are the normal state of rotor failure. In recent years, more and more attention has been paid to the fault detection method based on deep learning, which takes rotating machinery as the object. However, there is a lack of research on actual steam turbine rotors. In this paper, a method of rotor unbalance and parallel misalignment fault detection based on residual network is proposed, which realizes the end-to-end fault detection of rotor. Meanwhile, the method is evaluated with numerical simulation data, and the multi task detection of rotor unbalance, parallel misalignment, unbalanced parallel misalignment coupling faults (coupling fault called in this paper) is realized. The influence of signal-to-noise ratio and the number of training samples on the detection performance of neural network is discussed. The detection accuracy of unbalanced position is 93.5%, that of parallel misalignment is 99.1%. The detection accuracy for unbalance and parallel misalignment is 89.1% and 99.1%, respectively. The method can realize the direct mapping between the unbalanced, parallel misalignment, coupling fault vibration signals and the fault detection results. The method has the ability to automatically extract fault features. It overcomes the shortcoming of traditional methods that rely on signal processing experience, and has the characteristics of high precision and strong robustness.

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Reports on the topic "Simulation of fault signals"

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Venkataraman, Srikanth, W. K. Fuchs, and Janak H. Patel. Diagnostic Simulation of Sequential Circuits Using Fault Sampling. Fort Belvoir, VA: Defense Technical Information Center, January 1998. http://dx.doi.org/10.21236/ada339323.

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Johnson, Barry W., D. T. Smith, and Todd A. DeLong. VHDL Fault Simulation and Automatic Test Pattern Generation Requirements Document. Fort Belvoir, VA: Defense Technical Information Center, January 1996. http://dx.doi.org/10.21236/ada304358.

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DRAKE, RICHARD R., and RANDALL M. SUMMERS. An Exploration in Implementing Fault Tolerance in Scientific Simulation Application Software. Office of Scientific and Technical Information (OSTI), May 2003. http://dx.doi.org/10.2172/811162.

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Schein, Jeffery, and Steven Bushby. A simulation study of a hierarchical, rule-based method for system-level fault detection and diagnostics in HVAC systems. Gaithersburg, MD: National Institute of Standards and Technology, 2005. http://dx.doi.org/10.6028/nist.ir.7216.

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Juanes, Ruben. Enhanced Simulation Tools to Improve Predictions and Performance of Geologic Storage: Coupled Modeling of Fault Poromechanics, and High-Resolution Simulation of CO₂ Migration and Trapping. Office of Scientific and Technical Information (OSTI), December 2016. http://dx.doi.org/10.2172/1345666.

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Pitarka, Arben. Multi Segment Fault Rupture Modeling and Strong Ground Motion Simulation Using Irikura, Japan Recipe: Implementation in the in SCEC BB Platform. Office of Scientific and Technical Information (OSTI), April 2019. http://dx.doi.org/10.2172/1544495.

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Nafakh, Abdullah Jalal, Yunchang Zhang, Sarah Hubbard, and Jon D. Fricker. Assessment of a Displaced Pedestrian Crossing for Multilane Arterials. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317318.

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This research explores the benefits of a pedestrian crosswalk that is physically displaced from the intersection, using simulation software to estimate the benefits in terms of delay and pedestrian travel time. In many cases, the displaced pedestrian crossing may provide benefits such as reduced vehicle delay, reduced crossing distance, increased opportunity for signal progression, and reduced conflicts with turning vehicles. The concurrent pedestrian service that is traditionally used presents potential conflicts between pedestrians and three vehicular movements: right turns, permissive left turns, and right turns on red. The findings of this research suggest that a displaced pedestrian crossing should be considered as an option by designers when serving pedestrians crossing multi-lane arterials. In addition to reduced delay, pedestrian safety may be improved due to the shorter crossing distance, the elimination of conflicts with turning vehicles, and the potential for high driver compliance rates associated with signals, such as pedestrian hybrid beacons.

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Bobashev, Georgiy, John Holloway, Eric Solano, and Boris Gutkin. A Control Theory Model of Smoking. RTI Press, June 2017. http://dx.doi.org/10.3768/rtipress.2017.op.0040.1706.

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We present a heuristic control theory model that describes smoking under restricted and unrestricted access to cigarettes. The model is based on the allostasis theory and uses a formal representation of a multiscale opponent process. The model simulates smoking behavior of an individual and produces both short-term (“loading up” after not smoking for a while) and long-term smoking patterns (e.g., gradual transition from a few cigarettes to one pack a day). By introducing a formal representation of withdrawal- and craving-like processes, the model produces gradual increases over time in withdrawal- and craving-like signals associated with abstinence and shows that after 3 months of abstinence, craving disappears. The model was programmed as a computer application allowing users to select simulation scenarios. The application links images of brain regions that are activated during the binge/intoxication, withdrawal, or craving with corresponding simulated states. The model was calibrated to represent smoking patterns described in peer-reviewed literature; however, it is generic enough to be adapted to other drugs, including cocaine and opioids. Although the model does not mechanistically describe specific neurobiological processes, it can be useful in prevention and treatment practices as an illustration of drug-using behaviors and expected dynamics of withdrawal and craving during abstinence.

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