A single soft fault diagnosis method for analog circuit with tolerance based on particle swarm optimization(PSO)is proposed.The parameter deviation of circuit elements is defined as the element of particle.Node-voltag...A single soft fault diagnosis method for analog circuit with tolerance based on particle swarm optimization(PSO)is proposed.The parameter deviation of circuit elements is defined as the element of particle.Node-voltage incremental equations based on the sensitivity analysis are built as constraints of a linear programming(LP)equation.Through inducing the penalty coefficient,the LP equation is set as the fitness function for the PSO program.After evaluating the best position of particles,the position of the optimal particle states whether the actual parameter is within tolerance range or not.Simulation result shows the effectiveness of the method.展开更多
Fault diagnosis is very important for development and maintenance of safe and reliable electronic circuits and systems. This paper describes an approach of soft fault diagnosis for analog circuits based on slope fault...Fault diagnosis is very important for development and maintenance of safe and reliable electronic circuits and systems. This paper describes an approach of soft fault diagnosis for analog circuits based on slope fault feature and back propagation neural networks (BPNN). The reported approach uses the voltage relation function between two nodes as fault features; and for linear analog circuits, the voltage relation function is a linear function, thus the slope is invariant as fault feature. Therefore, a unified fault feature for both hard fault (open or short fault) and soft fault (parametric fault) is extracted. Unlike other NN-based diagnosis methods which utilize node voltages or frequency response as fault features, the reported BPNN is trained by the extracted feature vectors, the slope features are calculated by just simulating once for each component, and the trained BPNN can achieve all the soft faults diagnosis of the component. Experiments show that our approach is promising.展开更多
Soft fault compensation plays an important role in mobile robot locating, mapping, and navigating. It is difficult to achieve fast and accurate compensation for mobile robots because they are usually highly non-linear...Soft fault compensation plays an important role in mobile robot locating, mapping, and navigating. It is difficult to achieve fast and accurate compensation for mobile robots because they are usually highly non-linear, non-Gaussian systems with limited computation and memory resources. An adaptive particle filter is presented to compensate two kinds of soft faults for mobile robots, i.e., noise or factor faults of dead reckoning sensors and slippage of wheels. Firstly, the kinematics models and the fault models are discussed, and five kinds of residual features are extracted to detect soft faults. Secondly, an adaptive particle filter is designed for fault compensation, and two kinds of adaptive scheme are discussed： 1） the noise variances of linear speed and yaw rate are adjusted according to residual features; 2） the particle number is adapted according to Kullback-Leibler divergence （KLD） of two approximate distribution denoted with two particle sets with different particles, i.e., increasing particle number if the KLD is large and decreasing particle number if the KLD is small. The theoretic proof is given and experimental results show the efficiency and accuracy of the presented approach.展开更多
Aiming at the problem of diagnosing soft faults in analog integrated circuits, an approach based on fractional correlation is proposed. First, the Volterra series of the circuit under test （CUT） decomposed by the fr...Aiming at the problem of diagnosing soft faults in analog integrated circuits, an approach based on fractional correlation is proposed. First, the Volterra series of the circuit under test （CUT） decomposed by the fractional wavelet packet are used to calculate the fractional correlation functions. Then, the calculated fractional correlation functions are used to form the fault signatures of the CUT. By comparing the fault signatures, the different soft faulty conditions of the CUT are identified and the faults are located. Simulations of benchmark circuits illustrate the proposed method and validate its effectiveness in diagnosing soft faults in analog integrated circuits.展开更多
The soft fault induced by parameter variation is one of the most challenging problems in the domain of fault diagnosis for analog circuits.A new fault location and parameter prediction approach for soft-faults diagnos...The soft fault induced by parameter variation is one of the most challenging problems in the domain of fault diagnosis for analog circuits.A new fault location and parameter prediction approach for soft-faults diagnosis in analog circuits is presented in this paper.The proposed method extracts the original signals from the output terminals of the circuits under test（CUT） by a data acquisition board.Firstly,the phase deviation value between fault-free and faulty conditions is obtained by fitting the sampling sequence with a sine curve.Secondly,the sampling sequence is organized into a square matrix and the spectral radius of this matrix is obtained.Thirdly,the smallest error of the spectral radius and the corresponding component value are obtained through comparing the spectral radius and phase deviation value with the trend curves of them,respectively,which are calculated from the simulation data.Finally,the fault location is completed by using the smallest error,and the corresponding component value is the parameter identification result.Both simulated and experimental results show the effectiveness of the proposed approach.It is particularly suitable for the fault location and parameter identification for analog integrated circuits.展开更多
In this paper, the rupture characteristics of the overlaying soil with soft interlayer were studied by plane-strain finite element method. From the results, it can be shown that the existence of soft layer separates r...In this paper, the rupture characteristics of the overlaying soil with soft interlayer were studied by plane-strain finite element method. From the results, it can be shown that the existence of soft layer separates rupture process of the overlaying soil into two phases. The depth of a buried soft interlayer will influence the rupture process and the rupture range of the overlaying soil. The deeply buried soft interlayer would bring about a wider range of surface failure. In addition, the thickness of the soft layer also has effect on the rupture process and rupture range of the overlaying soil.展开更多
To deal with fault detection and diagnosis with incomplete model for dead reckoning system of mobile robot,an integrative framework of particle filter detection and fuzzy logic diagnosis was devised.Firstly,an adaptiv...To deal with fault detection and diagnosis with incomplete model for dead reckoning system of mobile robot,an integrative framework of particle filter detection and fuzzy logic diagnosis was devised.Firstly,an adaptive fault space is designed for recognizing both known faults and unknown faults,in corresponding modes of modeled and model-free.Secondly,the particle filter is utilized to diagnose the modeled faults and detect model-free fault according to the low particle weight and reliability.Especially,the proposed fuzzy logic diagnosis can further analyze model-free modes and identify some soft faults in unknown fault space.The MORCS-1 experimental results show that the fuzzy diagnosis particle filter(FDPF) combinational framework improves fault detection and identification completeness.Specifically speaking,FDPF is feasible to diagnose the modeled faults in known space.Furthermore,the types of model-free soft faults can also be further identified and diagnosed in unknown fault space.展开更多
针对煤矿井下电控系统中DC-DC电源模块电容软故障类型多样、诊断精度不足的问题,提出了一种基于并行时序卷积网络(TCN)与图卷积网络(GCN)的融合模型。以150 W Boost型DC-DC电源为研究对象,采集电路中4个测点的电压信号。该模型通过TCN...针对煤矿井下电控系统中DC-DC电源模块电容软故障类型多样、诊断精度不足的问题,提出了一种基于并行时序卷积网络(TCN)与图卷积网络(GCN)的融合模型。以150 W Boost型DC-DC电源为研究对象,采集电路中4个测点的电压信号。该模型通过TCN捕获长时依赖特征,以GCN刻画测点拓扑关系;二者在特征层拼接,实现时间维与空间结构信息的互补融合。实验结果表明,该模型平均准确率达99.72%;在6 dB、4 dB、2 dB、0 dB信噪比条件下,准确率分别达到99.48%、98.54%、98.17%和93.78%,高于其他模型。该研究为煤矿井下电控设备中电容软故障的智能诊断提供了有效技术路径。展开更多
Wind energy is one of the widely applied renewable energies in the world. Wind turbine as the main wind energy converter at present has very complex technical system containing a huge number of components,actuators an...Wind energy is one of the widely applied renewable energies in the world. Wind turbine as the main wind energy converter at present has very complex technical system containing a huge number of components,actuators and sensors. However, despite of the hardware redundancy, sensor faults have often affected the wind turbine normal operation and thus caused energy generation loss. In this paper, aiming at the wind turbine hydraulic pitch system, data-driven design of process monitoring(PM) and diagnosis has been realized in the wind turbine benchmark. Fault tolerant control(FTC) strategies focused on sensor faults have also been presented here, where with the implementation of soft sensor the sensor fault can be handled and the performance of the system is improved. The performance of this method is demonstrated with the wind turbine benchmark provided by Math Works.展开更多
Field Programmable Gate Arrays(FPGAs)offer high capability in implementing of complex systems,and currently are an attractive solution for space system electronics.However,FPGAs are susceptible to radiation induced Si...Field Programmable Gate Arrays(FPGAs)offer high capability in implementing of complex systems,and currently are an attractive solution for space system electronics.However,FPGAs are susceptible to radiation induced Single-Event Upsets(SEUs).To insure reliable operation of FPGA based systems in a harsh radiation environment,various SEU mitigation techniques have been provided.In this paper we propose a system based on dynamic partial reconfiguration capability of the modern devices to evaluate the SEU fault effect in FPGA.The proposed approach combines the fault injection controller with the host FPGA,and therefore the hardware complexity is minimized.All of the SEU injection and evaluation requirements are performed by a soft-core which realized inside the host FPGA.Experimental results on some standard benchmark circuits reveal that the proposed system is able to speed up the fault injection campaign 50 times in compared to conventional method.展开更多
Intervals of soft-sediment deformation structures are well-exposed in Jurassic lacustrine deposits in the western Qaidamu basin. Through field observation, many soft-sediment deformation structures can be identified, ...Intervals of soft-sediment deformation structures are well-exposed in Jurassic lacustrine deposits in the western Qaidamu basin. Through field observation, many soft-sediment deformation structures can be identified, such as convoluted bedding, liquefied sand veins, load and flame structures, slump structures and sliding-overlapping structures. Based on their genesis, soft-sediment deformation structures can be classified as three types： seismic induced structures, vertical loading structures, and horizontal shear structures. Based on their geometry and genesis analysis, they are seismic-induced structures. According to the characteristics of convoluted bedding structures and liquefied sand veins, it can be inferred that there were earthquakes greater than magnitude 6 in the study area during the middle Jurassic. Furthermore, the study of the slump structures and sliding- overlapping structures indicates that there was a southeastern slope during the middle Jurassic. Since the distance from the study area to the Altyn Mountain and the Altyn fault is no more than 10km, it can be also inferred that the Altyn Mountain existed then and that the AItyn strike-slip fault was active during the middle Jurassic.展开更多
基金supported by the Program for New Century Excellent Talents in University under Grant No.NCET-05-0804partly supported by Chinese National Programs for High Technology Research and Development under Grant No.2006AA06Z222
文摘A single soft fault diagnosis method for analog circuit with tolerance based on particle swarm optimization(PSO)is proposed.The parameter deviation of circuit elements is defined as the element of particle.Node-voltage incremental equations based on the sensitivity analysis are built as constraints of a linear programming(LP)equation.Through inducing the penalty coefficient,the LP equation is set as the fitness function for the PSO program.After evaluating the best position of particles,the position of the optimal particle states whether the actual parameter is within tolerance range or not.Simulation result shows the effectiveness of the method.
基金the National Basic Research and Development (973) Program of China (No.2005cb321604)the National Natural Science Foundation of China (No. 60633060)
文摘Fault diagnosis is very important for development and maintenance of safe and reliable electronic circuits and systems. This paper describes an approach of soft fault diagnosis for analog circuits based on slope fault feature and back propagation neural networks (BPNN). The reported approach uses the voltage relation function between two nodes as fault features; and for linear analog circuits, the voltage relation function is a linear function, thus the slope is invariant as fault feature. Therefore, a unified fault feature for both hard fault (open or short fault) and soft fault (parametric fault) is extracted. Unlike other NN-based diagnosis methods which utilize node voltages or frequency response as fault features, the reported BPNN is trained by the extracted feature vectors, the slope features are calculated by just simulating once for each component, and the trained BPNN can achieve all the soft faults diagnosis of the component. Experiments show that our approach is promising.
基金the National Natural Science Foundation of China (Grant No. 60234030)National Basic Research Project (Grant No. A1420060159)
文摘Soft fault compensation plays an important role in mobile robot locating, mapping, and navigating. It is difficult to achieve fast and accurate compensation for mobile robots because they are usually highly non-linear, non-Gaussian systems with limited computation and memory resources. An adaptive particle filter is presented to compensate two kinds of soft faults for mobile robots, i.e., noise or factor faults of dead reckoning sensors and slippage of wheels. Firstly, the kinematics models and the fault models are discussed, and five kinds of residual features are extracted to detect soft faults. Secondly, an adaptive particle filter is designed for fault compensation, and two kinds of adaptive scheme are discussed： 1） the noise variances of linear speed and yaw rate are adjusted according to residual features; 2） the particle number is adapted according to Kullback-Leibler divergence （KLD） of two approximate distribution denoted with two particle sets with different particles, i.e., increasing particle number if the KLD is large and decreasing particle number if the KLD is small. The theoretic proof is given and experimental results show the efficiency and accuracy of the presented approach.
基金Project supported by the Program for New Century Excellent Talents in University,China(No.NCET-05-0804)the Chinese National Programs for High Technology Research and Development(No.2006AA06Z222)
文摘Aiming at the problem of diagnosing soft faults in analog integrated circuits, an approach based on fractional correlation is proposed. First, the Volterra series of the circuit under test （CUT） decomposed by the fractional wavelet packet are used to calculate the fractional correlation functions. Then, the calculated fractional correlation functions are used to form the fault signatures of the CUT. By comparing the fault signatures, the different soft faulty conditions of the CUT are identified and the faults are located. Simulations of benchmark circuits illustrate the proposed method and validate its effectiveness in diagnosing soft faults in analog integrated circuits.
基金supported by the National Natural Science Foundation of China under Grant No.61371049
文摘The soft fault induced by parameter variation is one of the most challenging problems in the domain of fault diagnosis for analog circuits.A new fault location and parameter prediction approach for soft-faults diagnosis in analog circuits is presented in this paper.The proposed method extracts the original signals from the output terminals of the circuits under test（CUT） by a data acquisition board.Firstly,the phase deviation value between fault-free and faulty conditions is obtained by fitting the sampling sequence with a sine curve.Secondly,the sampling sequence is organized into a square matrix and the spectral radius of this matrix is obtained.Thirdly,the smallest error of the spectral radius and the corresponding component value are obtained through comparing the spectral radius and phase deviation value with the trend curves of them,respectively,which are calculated from the simulation data.Finally,the fault location is completed by using the smallest error,and the corresponding component value is the parameter identification result.Both simulated and experimental results show the effectiveness of the proposed approach.It is particularly suitable for the fault location and parameter identification for analog integrated circuits.
基金National Natural Science Foundation of China (50078049).
文摘In this paper, the rupture characteristics of the overlaying soil with soft interlayer were studied by plane-strain finite element method. From the results, it can be shown that the existence of soft layer separates rupture process of the overlaying soil into two phases. The depth of a buried soft interlayer will influence the rupture process and the rupture range of the overlaying soil. The deeply buried soft interlayer would bring about a wider range of surface failure. In addition, the thickness of the soft layer also has effect on the rupture process and rupture range of the overlaying soil.
基金Project(90820302) supported by the National Natural Science Foundation of ChinaProject(20110491272) supported by China Postdoctoral Science Foundation of China+2 种基金Project(2012QNZT060) supported by the Fundamental Research Fund for the Central Universities of ChinaProject(11B070) supported by the Science Research Foundation of Education Bureau of Hunan Province,ChinaProject(2010-2012) supported by the Postdoctoral Science Foundation of Central South University,China
文摘To deal with fault detection and diagnosis with incomplete model for dead reckoning system of mobile robot,an integrative framework of particle filter detection and fuzzy logic diagnosis was devised.Firstly,an adaptive fault space is designed for recognizing both known faults and unknown faults,in corresponding modes of modeled and model-free.Secondly,the particle filter is utilized to diagnose the modeled faults and detect model-free fault according to the low particle weight and reliability.Especially,the proposed fuzzy logic diagnosis can further analyze model-free modes and identify some soft faults in unknown fault space.The MORCS-1 experimental results show that the fuzzy diagnosis particle filter(FDPF) combinational framework improves fault detection and identification completeness.Specifically speaking,FDPF is feasible to diagnose the modeled faults in known space.Furthermore,the types of model-free soft faults can also be further identified and diagnosed in unknown fault space.
基金the National Natural Science Foundation of China(No.51205018)the Fundamental Research Funds for the Central Universities of China(No.FRF-TP-14-121A2)the Research Project of State Key Laboratory of Mechanical System and Vibration(No.MSV-2014-09)
文摘Wind energy is one of the widely applied renewable energies in the world. Wind turbine as the main wind energy converter at present has very complex technical system containing a huge number of components,actuators and sensors. However, despite of the hardware redundancy, sensor faults have often affected the wind turbine normal operation and thus caused energy generation loss. In this paper, aiming at the wind turbine hydraulic pitch system, data-driven design of process monitoring(PM) and diagnosis has been realized in the wind turbine benchmark. Fault tolerant control(FTC) strategies focused on sensor faults have also been presented here, where with the implementation of soft sensor the sensor fault can be handled and the performance of the system is improved. The performance of this method is demonstrated with the wind turbine benchmark provided by Math Works.
文摘Field Programmable Gate Arrays(FPGAs)offer high capability in implementing of complex systems,and currently are an attractive solution for space system electronics.However,FPGAs are susceptible to radiation induced Single-Event Upsets(SEUs).To insure reliable operation of FPGA based systems in a harsh radiation environment,various SEU mitigation techniques have been provided.In this paper we propose a system based on dynamic partial reconfiguration capability of the modern devices to evaluate the SEU fault effect in FPGA.The proposed approach combines the fault injection controller with the host FPGA,and therefore the hardware complexity is minimized.All of the SEU injection and evaluation requirements are performed by a soft-core which realized inside the host FPGA.Experimental results on some standard benchmark circuits reveal that the proposed system is able to speed up the fault injection campaign 50 times in compared to conventional method.
基金The National Natural Science Fund(No:41172093)the research fund(No:2003042500820060425509)for the doctoral program of higher education from Ministry of Education for their financial support
文摘Intervals of soft-sediment deformation structures are well-exposed in Jurassic lacustrine deposits in the western Qaidamu basin. Through field observation, many soft-sediment deformation structures can be identified, such as convoluted bedding, liquefied sand veins, load and flame structures, slump structures and sliding-overlapping structures. Based on their genesis, soft-sediment deformation structures can be classified as three types： seismic induced structures, vertical loading structures, and horizontal shear structures. Based on their geometry and genesis analysis, they are seismic-induced structures. According to the characteristics of convoluted bedding structures and liquefied sand veins, it can be inferred that there were earthquakes greater than magnitude 6 in the study area during the middle Jurassic. Furthermore, the study of the slump structures and sliding- overlapping structures indicates that there was a southeastern slope during the middle Jurassic. Since the distance from the study area to the Altyn Mountain and the Altyn fault is no more than 10km, it can be also inferred that the Altyn Mountain existed then and that the AItyn strike-slip fault was active during the middle Jurassic.
