Academic literature on the topic 'Fault simulation acceleration'
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Journal articles on the topic "Fault simulation acceleration"
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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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Li, Lingwei, Yuan Yuan, Xinglong Zhang, Songwei Wu, and Tianhong Zhang. "Fault-Tolerant Control Scheme for the Sensor Fault in the Acceleration Process of Variable Cycle Engine." Applied Sciences 12, no. 4 (February 17, 2022): 2085. http://dx.doi.org/10.3390/app12042085.
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This paper presents a fault-tolerant control scheme for the sensor fault in the acceleration process of the variable cycle engine. Firstly, an adaptive equilibrium manifold model with multiple inputs and multiple outputs is established. Combined with the Kalman filter bank, sensor fault diagnosis is carried out to realize the diagnosis and signal reconstruction of the engine in the case of a single sensor and double sensor faults. On this basis, isolation and group isolation are used to diagnose sensor faults and reconstruct signal in speed closed-loop control. Then, the control plan of the acceleration process is optimized based on the target shooting method, aiming to simulate the variation of various variables in the engine acceleration process more accurately, so as to verify the feasibility of the sensor fault-tolerant control scheme. Finally, a hardware-in-loop simulation platform is built based on the idea of distributed control, and the fault-tolerant control scheme of the sensor proposed previously is verified based on this platform. The results show that the proposed scheme can accurately diagnose the sensor faults and reconstruct the signal within 0.2 s, and the actual speed can rise from 67.87% to 99.9% in 4 s, ensuring the safe and rapid completion of the acceleration process.
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Yin, Zhengyang, Yi Yang, Guoji Shen, Ling Chen, and Niaoqing Hu. "Eight-DOF Dynamic Modeling of EMA Mechanical Transmission and Spalling Fault Characteristic Analysis." Actuators 11, no. 8 (August 6, 2022): 226. http://dx.doi.org/10.3390/act11080226.
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Electromechanical actuators (EMAs), as the critical actuator system of next-generation aircraft, have attracted the attention of many institutions and enterprises around the world. However, due to harsh working conditions, their reliability cannot satisfy the requirements of widespread application in aircraft. Therefore, in order to conduct fault diagnosis on EMAs, in this paper, we establish a comprehensive dynamic model under numerous assumptions to study the fault characteristics that may occur in the displacement and acceleration responses of EMA systems. First, an eight-DOF dynamic model containing typical mechanical components of an EMA is established. Then, by obtaining the impact forces between balls and the spalling fault and the nonlinear relationship between the total elastic restoring forces and the change of ball deformation when the fault occurs, a faulty dynamic model is established. Comparison of the simulation results between the normal and faulty model reveals that the acceleration amplitude at the third harmonic of the ball passage frequency increases when fault occurs. Based on this phenomenon, a numerical calculation method of fault characteristics is proposed. Finally, the effectiveness of the established models and the identified phenomenon are verified by experiments conducted on an EMA test rig in a laboratory environment.
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Song, O. Y., and P. R. Menon. "Acceleration of trace-based fault simulation of combinational circuits." IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 12, no. 9 (1993): 1413–19. http://dx.doi.org/10.1109/43.240089.
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Rogers, A. M., and D. M. Perkins. "Monte Carlo simulation of peak-acceleration attenuation using a finite-fault uniform-patch model including isochrone and extremal characteristics." Bulletin of the Seismological Society of America 86, no. 1A (February 1, 1996): 79–92. http://dx.doi.org/10.1785/bssa08601a0079.
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Abstract A finite-fault statistical model of the earthquake source is used to confirm observed magnitude and distance saturation scaling in a large peak-acceleration data set. This model allows us to determine the form of peak-acceleration attenuation curves without a priori assumptions about their shape or scaling properties. The source is composed of patches having uniform size and statistical properties. The primary source parameters are the patch peak-acceleration distribution mean, the distribution standard deviation, the patch size, and patch-rupture duration. Although our model assumes no scaling of peak acceleration with magnitude at the patch, the peak-acceleration attenuation curves, nevertheless, strongly scale with magnitude (dap/dM) ≠ 0, and the scaling is distance dependent (dap/dM) ∝ f(r). The distance-dependent magnitude scaling arises from two principal sources in the model. For a propagating rupture, loci exist on the fault from which radiated energy arrives at a particular station at the same time. These loci are referred to as isochrones. As fault size increases, the length of the isochrones and, hence, the number of additive pulses increase. Thus, peak accelerations increase with magnitude. The second effect, which arises in a completely different manner, is due to extreme-value properties. That is, as the fault size increases, the number of patches on the fault and the number of peak values at the station increase. Because these attenuated pulses are produced by a statistical distribution at the patch, the largest value will depend on the total number of peak values available on the seismogram. We refer to this result as the extremal effect, because it is predicted by the theory of extreme values. Both the extremal and isochrone effects are moderated by attenuation and distance to the fault, leading to magnitude- and distance-dependent peak-acceleration scaling. Remarkably, the scaling produced by both effects is very similar, although the underlying mechanisms are completely different. Because this model approximates data characteristics we have observed in an earlier study, we adjusted the parameters of the model to fit a set of smoothed peak accelerations from earthquakes worldwide. These data have not been preselected for particular magnitude or distance ranges and contain earthquake records for magnitudes ranging from about M 3 to M 8 and distance ranging from a few kilometers to about 400 km. In fitting the data, we use a trial-and-error procedure, varying the mean and standard deviation of the patch peak-acceleration distribution, the patch size, and the pulse duration. The model explicitly includes triggering bias, and the triggering threshold is also a model parameter. The data can be approximated equally well by a model that includes the isochrone effect alone, the extremal effect alone, or both effects. Inclusion of both effects is likely to be closest to reality, but because both effects produce similar results, it is not possible to determine the relative contribution of each one. In any case, the model approximates the complex features of the observed data, including a decrease in magnitude scaling with increasing magnitude at short distances and increase in magnitude scaling with magnitude at large distances.
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Liu, Shulian, Ling Zhang, Likang Yang, Cunkai Gu, and Zaihua Wang. "The Identification Method of the Winding Vibration Faults of Dry-Type Transformers." Electronics 12, no. 1 (December 20, 2022): 3. http://dx.doi.org/10.3390/electronics12010003.
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To identify the four typical faults of dry-type transformer winding insulations, looseness, deformation and eccentricity, this study establishes the electric magnetic force multi-physical field simulation model of a dry-type transformer winding under the four typical faults with COMSOL software, based on the vibration mechanism of an SCB10-1000/10 dry-type transformer. Through the multi-physical field coupling calculation, the comparative relationship between the vibration acceleration of the winding under the four kinds of faults and the normal working state is obtained. The results show that the amplitude growth rate of the fundamental frequency or harmonic frequency of the acceleration signal under four kinds of faults is different from that under normal conditions. Therefore, the threshold value of the fundamental frequency or harmonic increment of the acceleration signal is introduced to describe the growth rate of the acceleration signal relative to normal conditions. Finally, four typical faults are identified with different threshold ranges of acceleration increment under faults, laying a foundation for the fault diagnosis of transformer winding vibrations.
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Zhang, Hehong, Yunde Xie, and Zhiqiang Long. "Fault Detection Based on Tracking Differentiator Applied on the Suspension System of Maglev Train." Mathematical Problems in Engineering 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/242431.
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A fault detection method based on the optimized tracking differentiator is introduced. It is applied on the acceleration sensor of the suspension system of maglev train. It detects the fault of the acceleration sensor by comparing the acceleration integral signal with the speed signal obtained by the optimized tracking differentiator. This paper optimizes the control variable when the states locate within or beyond the two-step reachable region to improve the performance of the approximate linear discrete tracking differentiator. Fault-tolerant control has been conducted by feedback based on the speed signal acquired from the optimized tracking differentiator when the acceleration sensor fails. The simulation and experiment results show the practical usefulness of the presented method.
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Du, Can Yi, and Fei Fei Yu. "Analysis of Engine Camshaft Bearing Loosening Fault Based-on Model Simulation and Vibration Signal." Advanced Materials Research 694-697 (May 2013): 896–900. http://dx.doi.org/10.4028/www.scientific.net/amr.694-697.896.
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Virtual technology is used for simulation analysis of engine camshaft bearing-loosening fault. Firstly, dynamic model of engine powertrain and its valve-train is established, and then the model parameters could be set to simulate the camshaft bearing loosening fault, so the vibration acceleration signals on engine cylinder head can be obtained by simulation calculation. Then by analyzing and comparing with the vibration signals in the normal state, camshaft bearing-loosening fault features are extracted. The analytical result based-on model simulation and vibration signal is used to guide the actual engine fault diagnosis.
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ISUMI, MASANORI, HIROSHI KATSUKURA, and YOUICHI HAGINO. "STUDY ON THE SIMULATION OF ACCELERATION ENVELOPES BY FAULT MODELS." Journal of Structural and Construction Engineering (Transactions of AIJ) 348 (1985): 26–32. http://dx.doi.org/10.3130/aijsx.348.0_26.
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Chen, Jian, Robert Randall, Ningsheng Feng, Bart Peeters, and Herman Van der Auweraer. "Modelling and diagnosis of big-end bearing knock fault in internal combustion engines." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 228, no. 16 (February 24, 2014): 2973–84. http://dx.doi.org/10.1177/0954406214524743.
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Big-end bearing knock is considered to be one of the common mechanical faults in internal combustion engines (IC engines). In this paper, a model has been built to simulate the effects of oversized clearance in the big-end bearing of an engine. In order to find a relationship between the acceleration response signal and the oversized clearance, the kinematic/kinetic and lubrication characteristics of the big ending bearing were studied. By adjusting the clearance, the impact forces with different levels of bearing knock fault can be simulated. The acceleration on the surface of the engine block was calculated by multiplying the simulated force spectrum by an experimentally measured frequency response function (FRF) in the frequency domain (and then inverse transforming to the time domain). As for experimentally measured vibration signals from bearing knock faults, the signal processing approach used involved calculating the squared envelopes of the simulated acceleration signals. The comparison to the experimental results demonstrated that the simulation model can correctly simulate vibration signals with different stages of bearing knock faults.
Dissertations / Theses on the topic "Fault simulation acceleration"
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Li, Min. "Acceleration of Hardware Testing and Validation Algorithms using Graphics Processing Units." Diss., Virginia Tech, 2012. http://hdl.handle.net/10919/29129.
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With the advances of very large scale integration (VLSI) technology, the feature size has been shrinking steadily together with the increase in the design complexity of logic circuits. As a result, the efforts taken for designing, testing, and debugging digital systems have increased tremendously. Although the electronic design automation (EDA) algorithms have been studied extensively to accelerate such processes, some computational intensive applications still take long execution times. This is especially the case for testing and validation. In order tomeet the time-to-market constraints and also to come up with a bug-free design or product, the work presented in this dissertation studies the acceleration of EDA algorithms on Graphics Processing Units (GPUs). This dissertation concentrates on a subset of EDA algorithms related to testing and validation. In particular, within the area of testing, fault simulation, diagnostic simulation and reliability analysis are explored. We also investigated the approaches to parallelize state justification on GPUs, which is one of the most difficult problems in the validation area.
Firstly, we present an efficient parallel fault simulator, FSimGP2, which exploits the high degree of parallelism supported by a state-of-the-art graphic processing unit (GPU) with the NVIDIA Compute Unified Device Architecture (CUDA). A novel three-dimensional parallel fault simulation technique is proposed to achieve extremely high computation efficiency on the GPU. The experimental results demonstrate a speedup of up to 4Ã compared to another GPU-based fault simulator.
Then, another GPU based simulator is used to tackle an even more computation-intensive task, diagnostic fault simulation. The simulator is based on a two-stage framework which exploits high computation efficiency on the GPU. We introduce a fault pair based approach to alleviate the limited memory capacity on GPUs. Also, multi-fault-signature and dynamic load balancing techniques are introduced for the best usage of computing resources on-board.
With continuously feature size scaling and advent of innovative nano-scale devices, the reliability analysis of the digital systems becomes more important nowadays. However, the computational cost to accurately analyze a large digital system is very high. We proposes an high performance reliability analysis tool on GPUs. To achieve highmemory bandwidth on GPUs, two algorithms for simulation scheduling and memory arrangement are proposed. Experimental results demonstrate that the parallel analysis tool is efficient, reliable and scalable.
In the area of design validation, we investigate state justification. By employing the swarm intelligence and the power of parallelism on GPUs, we are able to efficiently find a trace that could help us reach the corner cases during the validation of a digital system.
In summary, the work presented in this dissertation demonstrates that several applications in the area of digital design testing and validation can be successfully rearchitected to achieve maximal performance on GPUs and obtain significant speedups. The proposed algorithms based on GPU parallelism collectively aim to contribute to improving the performance of EDA tools in Computer aided design (CAD) community on GPUs and other many-core platforms.Ph. D.
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Gulati, Kanupriya. "Hardware Acceleration of Electronic Design Automation Algorithms." 2009. http://hdl.handle.net/1969.1/ETD-TAMU-2009-12-7471.
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With the advances in very large scale integration (VLSI) technology, hardware is going
parallel. Software, which was traditionally designed to execute on single core microprocessors,
now faces the tough challenge of taking advantage of this parallelism, made available
by the scaling of hardware. The work presented in this dissertation studies the acceleration
of electronic design automation (EDA) software on several hardware platforms such
as custom integrated circuits (ICs), field programmable gate arrays (FPGAs) and graphics
processors. This dissertation concentrates on a subset of EDA algorithms which are heavily
used in the VLSI design flow, and also have varying degrees of inherent parallelism
in them. In particular, Boolean satisfiability, Monte Carlo based statistical static timing
analysis, circuit simulation, fault simulation and fault table generation are explored. The
architectural and performance tradeoffs of implementing the above applications on these
alternative platforms (in comparison to their implementation on a single core microprocessor)
are studied. In addition, this dissertation also presents an automated approach to
accelerate uniprocessor code using a graphics processing unit (GPU). The key idea is to
partition the software application into kernels in an automated fashion, such that multiple
instances of these kernels, when executed in parallel on the GPU, can maximally benefit
from the GPU?s hardware resources.
The work presented in this dissertation demonstrates that several EDA algorithms can
be successfully rearchitected to maximally harness their performance on alternative platforms
such as custom designed ICs, FPGAs and graphic processors, and obtain speedups upto 800X. The approaches in this dissertation collectively aim to contribute towards enabling
the computer aided design (CAD) community to accelerate EDA algorithms on arbitrary
hardware platforms.
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Yuan, Yi. "A microprocessor performance and reliability simulation framework using the speculative functional-first methodology." Thesis, 2011. http://hdl.handle.net/2152/ETD-UT-2011-12-4848.
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With the high complexity of modern day microprocessors and the slow speed of cycle-accurate simulations, architects are often unable to adequately evaluate their designs during the architectural exploration phases of chip design. This thesis presents the design and implementation of the timing partition of the cycle-accurate, microarchitecture-level SFFSim-Bear simulator. SFFSim-Bear is an implementation of the speculative functional-first (SFF) methodology, and utilizes a hybrid software-FPGA platform to accelerate simulation throughput. The timing partition, implemented in FPGA, features throughput-oriented, latency-tolerant designs to cope with the challenges of the hybrid platform. Furthermore, a fault injection framework is added to this implementation that allows designers to study the reliability aspects of their processors. The result is a simulator that is fast, accurate, flexible, and extensible.text
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Lee, Ten_Hwang, and 李增煌. "Realization of a Parallel-Pattern Parallel-Fault Fault Simulation Accelerator for Synchronous Sequential Circuits." Thesis, 1997. http://ndltd.ncl.edu.tw/handle/93417557794494497841.
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碩士國立交通大學
電子工程學系
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In this thesis, we realize the hardware design and circuit simulation of a zero delay fault simulation hardware accelerator for the gate level synchronoussequential circuits. A parallel sequence fault simulation algorithm is used toachieve parallel-pattern fault simulation, and multiple processing elementsare used to achieve the parallel-fault fault simulation. As to detailed architectural and hardware design, we adopt several specific methodologiesand design approaches to fulfill the hardware fault simulation andaccelerate its performance. The proposed architecture is implemented inVerilog hardware description language and targeted for Compass 0.6u cell library. When the accelerator being configured as single PE, its performanceruns at an average from 1.95E+07 G*V/s to 8.22E+07 G* V/s. It's about 20 to 80times of software simulators. A speedup of 6.96 in average can be reached ifit is configured as 16 PEs.
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Lai, Yin-chao, and 賴盈兆. "VLSI Implementation of a Fault Simulation Accelerator using Cellular Automata." Thesis, 1995. http://ndltd.ncl.edu.tw/handle/04381550122382075952.
Full textBooks on the topic "Fault simulation acceleration"
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M, Perkins David, and Geological Survey (U.S.), eds. Monte Carlo simulation of peak-acceleration attenuation using a finite-fault uniform-patch model: A parameter study. [Reston, Va.?]: Dept. of the Interior, U.S. Geological Survey, 1995.
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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.
Find full textBook chapters on the topic "Fault simulation acceleration"
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Gulati, Kanupriya, and Sunil P. Khatri. "Accelerating Fault Simulation Using Graphics Processors." In Hardware Acceleration of EDA Algorithms, 119–32. Boston, MA: Springer US, 2010. http://dx.doi.org/10.1007/978-1-4419-0944-2_8.
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Li, Lili, Hao Luo, He Qi, and Feiyu Wang. "Sensor Fault Diagnosis Method of Bridge Monitoring System Based on FS-LSTM." In Advances in Frontier Research on Engineering Structures, 487–501. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-8657-4_44.
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AbstractAn improved long-short-term memory neural network (FS-LSTM) fault diagnosis method is proposed based on the problems of damage false alarm, data of health monitoring system incorrect caused by sensor fault in bridge structure health monitoring system. The method is verified by simulating three-span continuous beams to install several sensors and considering the five failures of one sensor, the faults such as: constant, gain, bias, gain linearity bias, and noise. At first, several pieces of white noise data are randomly generated, and each piece of white noise data is applied as a ground pulsation excitation to the structure support, and the acceleration response of the structure at the sensor location is calculated. Simultaneously, each structural response record of each sensor adds white noise with the same signal-to-noise ratio to obtain the test value of each sensor; Secondly, in order to study the generality, except for the five types of faulty sensors in sequence, one sensor is randomly selected from each of the remaining spans, to verify whether there will be a situation where an intact sensor is misdiagnosed as a faulty sensor; Finally, the FS-LSTM network is constructed through the training set to predict the acceleration data, determine the sensor fault threshold, and compare the residual sequence with the fault threshold to diagnose whether the sensor is faulty. The case research of a three-span continuous beam shows that when the above-mentioned five types of faults occur in the sensor, the proposed method can correctly determine whether the sensor is faulty, and it will not be misdiagnosed, which can be used for daily bridge health monitoring. Furthermore, it provides a new method for the maintenance of the bridge health monitoring system.
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Gong, Yansheng, and Wenfeng Jing. "Research on 1D-CNN Detection Methods of High-Speed Railway Catenary Dropper Faults Based on Acceleration Sensors." In Advances in Transdisciplinary Engineering. IOS Press, 2022. http://dx.doi.org/10.3233/atde220071.
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Droppers are key components of high-speed railway overhead catenary systems, which are exposed to the external environment and are prone to breakage faults due to the impact of wind force and the pantograph on moving trains day after day. How to identify dropper breakage or relaxation faults through acceleration signals installed in the carrier cable and contact wire is a challenging problem. In this study, the experimental section of the Lanzhou-Xinjiang high-speed railway was simulated on the basis of the bow-network dynamic simulation model, in which the overhead catenary system was subjected to the force of pulsating wind alone or pulsating wind and the pantograph at the same time. In the experiment, we collected 10 channel signals from five acceleration sensors when two droppers were normal or broken. We established a 1D-CNN model of four categories and then determined the hyperparameters of the deep network structure and the important parameters of the network optimization scheme through the Bayesian optimization algorithm. Furthermore, we selected the lowest sensor number to identify dropper fracture faults by a large number of experiments according to mechanics principles. The experimental results show that the proposed methods have a higher identification accuracy rate, recall rate, and robustness than the traditional artificial feature extraction approaches. Therefore, the detection methods proposed provide an effective way to identify high-speed railway catenary dropper faults on the basis of acceleration sensors.
Conference papers on the topic "Fault simulation acceleration"
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Gulati, Kanupriya, and Sunil P. Khatri. "Towards acceleration of fault simulation using graphics processing units." In the 45th annual conference. New York, New York, USA: ACM Press, 2008. http://dx.doi.org/10.1145/1391469.1391679.
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Beckler, Matthew, and R. D. Blanton. "Fault simulation acceleration for TRAX dictionary construction using GPUs." In 2017 IEEE International Test Conference (ITC). IEEE, 2017. http://dx.doi.org/10.1109/test.2017.8242078.
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Lu, Xiao-Yun, and J. Karl Hedrick. "A Panoramic View of Fault Management for Longitudinal Control of Automated Vehicle Platooning." In ASME 2002 International Mechanical Engineering Congress and Exposition. ASMEDC, 2002. http://dx.doi.org/10.1115/imece2002-32106.
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This paper proposes some principles for fault management of longitudinal control of automated vehicles in AHS. Systems faults may be broadly divided into software and hardware. Software fault management is briefly addressed. These faults can be avoided by proper controller design, rigorous algorithm development, correct and robust code construction, simulation and real-time run test. Emphases are put on hardware faults. Hardware faults which may appear in practice are classified according to their likelihood of appearance, impact on safety, robust stability within controller bandwidth and maneuverability. The most prominent cases are those when communication and/or radar are in fault. From control viewpoint, they have very strong impact on string stability. The main difficulties in these cases are: (a) Some or all of the three parameters: relative distance, speed and acceleration, are not directly available; (b) Measurements of these parameters contains some noise; (c) Filtering and estimation of these parameters lead to some time delay and discrepancy. General principle of control strategy for each fault case is proposed. Corresponding string stability of the platoon is briefly analyzed. Consideration in this paper is in higher level. To practically implement each of these strategies will be addressed in future works.
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White, Maurice F. "An Investigation of Component Deterioration in Gas Turbines Using Transient Performance Simulation." In ASME 1988 International Gas Turbine and Aeroengine Congress and Exposition. American Society of Mechanical Engineers, 1988. http://dx.doi.org/10.1115/88-gt-258.
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This paper discusses a program which has been developed for the prediction of steady state and transient performance of a gas turbine driven generator. The gas turbine plant was modelled using the component model principle and is based on the method for continuity of mass flow. The model requires the use of compressor and turbine characteristics together with curves for combustion efficiency. A number of simplifications are made in connecion with transient calculations. The influence of the machines physical volume on continuity of mass flow and effects of heat transfer between the gas and structural components are neglected. The model was used to investigate how component deterioration affects the important condition parameters during load transients and during rapid acceleration or deceleration. Fault conditions were simulated by manipulating the various efficiencies and loss factors for the different components in the machine. Many of the condition parameters that were investigated showed changes during acceleration which were considerably different from comparable changes in a fault free gas turbine.
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Rueda Villanoba, Sergio Alberto, and Carlos Borrás Pinilla. "Neural Network Based Fault Tolerant Control for a Semi-Active Suspension." In ASME 2019 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/imece2019-11516.
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Abstract In this study a Neural Network based fault tolerant control is proposed to accommodate oil leakages in a magnetorheological suspension system based in a half car dynamic model. This model consists of vehicle body (spring mass) connected by the MR suspension system to two lateral wheels (unsprung mass). The semi-active suspension system is a four states nonlinear model; it can be written as a state space representation. The main objectives of a suspension are: Isolate the chassis from road disturbances (passenger comfort) and maintain contact between tire and road to provide better maneuverability, safety and performance. On the other hand, component faults/failures are inevitable in all practical systems, the shock absorbers of semi-active suspensions are prone to fail due to fluid leakage but quickly detect and diagnose this fault in the system, avoid major damage to the system and ensure the safety of the driver. To successfully achieve desirable control performance, it is necessary to have a damping force model which can accurately represent the highly nonlinear and hysteretic dynamic of the MR damper. To simulate parameters of the damper, a quasi-static model was applied, quasi-static approaches are based on non-newtonian yield stress fluids flow by using the Bingham MR Damper Model, relating the relative displacement of the piston, the frictional force, a damping constant, the stiffness of the elastic element of the damper and an offset force. The Fault detection and isolation module is based on residual generation algorithms. The residua r is computed as the difference between the displacement signal of functional and faulty model, when the residual is close to zero, the process is free of faults, while any change in r represents a faulty scheme then a wavelet transform, (Morlet wave function) is used to determine the natural frequencies and amplitudes of displacement and acceleration signal during the failure, this module provides parameters to the neural network controller in order to accommodate the failure using compensation forces from the remaining healthy damper. The neural network uses the error between the plant output and the neural network plant for computing the required electric current to correct the malfunction using the inverse dynamics function of the MR damper model. Consequently, a bump condition, and a random profile road (ISO 8608) described by the power spectral density (PSD) of its vertical displacement, is used as disturbance of control system. The performance of the proposed FTC structure is demonstrated trough simulation. Results shows that the control system could reduce the effect of the partial fault of the MR Damper on system performance.
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Sankar, Balaji, Thennavarajan Subramanian, Brijeshkumar Shah, Vijayendranath Vanam, Soumendu Jana, Srinivisan Ramamurthy, Radhakant Satpathy, Benudhar Sahoo, and Satish Yadav. "Aero-Thermodynamic Modelling and Gas Path Simulation for a Twin Spool Turbo Jet Engine." In ASME 2013 Gas Turbine India Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/gtindia2013-3643.
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The user community of civil and military aircraft powered by gas turbine engines has a significant interest on simulation models for design, development and maintenance activities. These play a crucial role in understanding the aircraft mission performance. The simulation models can be used to understand the behavior of gas turbine engine running at various operating conditions, which are used for studying the aircraft performance and also vital for engine diagnostics. Other significant advantage of simulation model is that it can generate required data at intermediate stages in gas turbine engine, which sometimes cannot be obtained by measurement. Thus engine simulation model / virtual engine building is one of the important aspects towards development of Engine Health Management (EHM) system. This paper describes in detail the engine simulation model development for a typical twin spool turbo jet engine using commercially available Gas turbine Simulation Program (GSP). The engine simulation model has been used for typical aero-engine to get aero-thermodynamic gas path performance analysis related to engine run at Design point, Off Design points and the engine Acceleration-Deceleration Cycles (ADC). Simulations at different operating conditions have been carried out using scaled up characteristic maps of engine components. Design point data as well as engine gas path data obtained from test bed has been used to develop scaled up characteristic maps of the engine components. The simulation results have been compared with various test bed data sets for the purpose of validation. Predicted results of engine parameters like engine mass flow rate and thrust are in good agreement with the test bed data. This validated model can be used to simulate faulty engine components and to develop the fault identification modules and subsequently an EHM system.
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Kubo, Kotaro, Keita Fujiwara, Yoichi Tanaka, Yuto Hakuta, Daisuke Arake, Tomoaki Uchiyama, and Ken Muramatsu. "A Scoping Study on the Use of Direct Quantification of Fault Tree Using Monte Carlo Simulation in Seismic Probabilistic Risk Assessments." In 2022 29th International Conference on Nuclear Engineering. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/icone29-88773.
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Abstract After the Fukushima Daiichi Nuclear Power Plant accident, the importance of conducting probabilistic risk assessments (PRAs) of external events, especially seismic activities and tsunamis, was recognized. The Japan Atomic Energy Agency has been developing a computational methodology for seismic PRA, called the direct quantification of fault tree using Monte Carlo simulation (DQFM). When appropriate correlation matrices are available for seismic responses and capacities of components, the DQFM makes it possible to consider the effect of correlated failures of components connected through AND and/or OR gates in fault trees, which is practically difficult when methods using analytical solutions or multidimensional numerical integrations are used to obtain minimal cut set probabilities. The usefulness of DQFM has already been demonstrated. Nevertheless, a reduction of the computational time of DQFM would allow the large number of analyses required in PRAs conducted by regulators and/or operators. We therefore performed scoping calculations using three different approaches, namely quasi-Monte Carlo sampling, importance sampling, and parallel computing, to improve calculation efficiency. These were applied when calculating the conditional core damage probability of a simplified PRA model of a pressurized water reactor, using the DQFM method. The results indicated that the quasi-Monte Carlo sampling works well at assumed medium and high ground motion levels, the importance sampling is suitable for assumed low ground motion level, and that the parallel computing enables practical uncertainty and importance analyses. The combined implementation of these improvements in a PRA code is expected to provide a significant acceleration of computation and offers the prospect of practical use of DQFM in risk-informed decision-making.
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Liu, Honghai, and George M. Coghill. "Connecting Quantitive Data and Qualitative States for Robotic Systems." In ASME 2004 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2004. http://dx.doi.org/10.1115/detc2004-57172.
Full textAbstract:
This study presents an approach, the unit circle (UC), to bridge numerical data from each variable of robotic systems and its corresponding qualitative state so that current qualitative methods (e.g. fuzzy models) can apply to general robotic systems. A manipulator is described as a collection of constraints holding among time-varying, interval-valued parameters. The UC representation is presented, and the continuous motion of the end-effector is evaluated by the change of directions of qualitative angle and qualitative length. Analytical formulas of qualitative velocity and qualitative acceleration are derived. The characteristic mapping is introduced for fault detection and diagnosis in terms of the UC. In the end simulation results demonstrate the feasibility of the UC approach for fault diagnosis. The UC representation of robots concerns a global assessment of the systems behaviour, and it might be used for the purpose of monitoring, diagnosis, and explanation of physical systems. This is the first step to fault diagnosis and remediation for robots (e.g. Beagle 2) using qualitative methods.
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Zhang, Jiyu, Alessandro Amodio, Bilin Aksun Guvenc, Giorgio Rizzoni, and Pierluigi Pisu. "Investigation of Torque Security Problems in Electrified Vehicles." In ASME 2015 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/dscc2015-9627.
Full textAbstract:
Functional safety of hybrid electric and electric vehicles has attracted a great deal of attention among automobile industries worldwide. Torque security is one of the main hazards that should be considered for functional safety of electrified vehicles. Over the past decades, a significant number of accidents have been reported to be caused by unintended acceleration that results from torque security problems. This paper investigates the factors related to torque security problems in electric vehicles using the Failure Modes and Effect Analysis (FMEA) approach. The fault scenarios that can potentially result in loss of torque security in electrified vehicles are evaluated in a simulation study.
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Wang, Chunjian, Beshah Ayalew, and Zoran Filipi. "Fault Diagnosis on a Digital-Displacement Pump/Motor." In ASME 2013 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/dscc2013-3967.
Full textAbstract:
A Digital-Displacement Pump/Motor (DDPM) has recently been proposed as an attractive candidate for hydraulic powertrain applications. A DDPM uses solenoid-controlled valves for each cylinder. This provision offers flexibility of control that can be exploited to boost system efficiency by matching individual cylinder operations with load conditions. However, the added complexity from individual cylinder control necessitates mechanisms for fault diagnosis and control reconfiguration to ensure reliable operation of the DDPM. Furthermore, available measurements are often limited to supply and return line pressures, shaft angle and speed. In this paper, it is shown that, with only these measurements, individual cylinder faults are structurally unobservable and un-isolable by the use of a system model relating the cylinder faults to the shaft dynamics. To overcome this difficulty, the phase angles at which possible individual cylinder faults can begin to affect the shaft dynamics are tabulated for each cylinder, and a fault indicator that is akin to a shaft acceleration fault is modeled and estimated via a fast sliding mode observer. Simultaneous detection and isolation of individual cylinder faults can be achieved using this fault indicator and a table of fault begin angles. Illustrative examples are included from simulations of a 5 cylinder DDPM to demonstrate this diagnosis process.