Arc fault detection is desperately required in Solid State Power Controllers（SSPC） in addition to their fundamental functions because arcs will provoke growing harm and threat to aircraft safety. Experimental study ...Arc fault detection is desperately required in Solid State Power Controllers（SSPC） in addition to their fundamental functions because arcs will provoke growing harm and threat to aircraft safety. Experimental study has been done to obtain the faulted current data. In order to improve the detection speed and accuracy, two fast arc fault detection methods have been proposed in this paper with the analysis of only half cycle data. Both Fast Fourier Transform（FFT） and Wavelet Packets Decomposition（WPD） have been adopted to distinguish arc fault currents from normal operation currents. Analysis results show that Alternating Current（AC） arcs can be effectively and accurately detected with the proposed half cycle data based methods. Moreover,experimental verification results have also been provided.展开更多
The influence of random short time-delay to networked control systems （NCS） is changed into an unknown bounded uncertain part. Without changing the structure of the system, an Hoo states observer is designed for NCS...The influence of random short time-delay to networked control systems （NCS） is changed into an unknown bounded uncertain part. Without changing the structure of the system, an Hoo states observer is designed for NCS with short time-delay. Based on the designed states observer, a robust fault detection approach is proposed for NCS. In addition, an optimization method for the selection of the detection threshold is introduced for better tradeoff between the robustness and the sensitivity. Finally, some simulation results demonstrate that the presented states observer is robust and the fault detection for NCS is effective.展开更多
A parametric approach to robust fault detection in linear systems with unknown disturbances is presented.The residual is generated using full-order state observers(FSO).Based on an analytical solution to a type of Syl...A parametric approach to robust fault detection in linear systems with unknown disturbances is presented.The residual is generated using full-order state observers(FSO).Based on an analytical solution to a type of Sylvester matrix equations,the parameterization of the observer gain matrix is given.In terms of the design degrees of freedom provided by the parametric observer design and a group of introduced parameter vectors,a sufficient and necessary condition for fullorder state observer design with disturbance decoupling is then established.By properly constraining the design parameters according to this proposed condition,the effect of the disturbance on the residual signal is also decoupled,and a simple algorithm is developed.The presented approach offers all the degrees of design freedom.Finally,a numerical example illustrates the effect of the proposed approach.展开更多
Rotating systems have many applications in wide-ranging industrial contexts. The breakdown of this equipment results in economic wastes and leads to dangerous situations. To avoid such problems is very important, and ...Rotating systems have many applications in wide-ranging industrial contexts. The breakdown of this equipment results in economic wastes and leads to dangerous situations. To avoid such problems is very important, and it can be done through tools that inform about the existence of faults, as well as, about their progress in time. A review of the modeling process used for rotor-support-structure shows that the finite element method is the maj or method employed. In this paper, with the aid of well defined theoretical models, obtained using the finite element technique, and the state observer method for the identification and location of faults, it is possible to monitor the parameters of a rotor-support-structure system, including the foundation effects. In order to improve safety, these parameters must be supervised in case of the occurrence of failures or faults. The state observers are designed using Linear Matrix Inequalities （LMIs）. Finally, experimental results （using for this a rotation system in the mechanical vibrations laboratory at Ilha Solteira＇s Mechanical Engineering Department） demonstrate the effectiveness of the methodology developed.展开更多
Monolithic three-dimensional integrated circuits(M3D ICs)have emerged as an innovative solution to overcome the limitations of traditional 2D scaling,offering improved performance,reduced power consumption,and enhance...Monolithic three-dimensional integrated circuits(M3D ICs)have emerged as an innovative solution to overcome the limitations of traditional 2D scaling,offering improved performance,reduced power consumption,and enhanced functionality.Inter-layer vias(ILVs),crucial components of M3D ICs,provide vertical connectivity between layers but are susceptible to manufacturing and operational defects,such as stuck-at faults(SAFs),shorts,and opens,which can compromise system reliability.These challenges necessitate advanced built-in self-test(BIST)methodologies to ensure robust fault detection and localization while minimizing the testing overhead.In this paper,we introduce a novel BIST architecture tailored to efficiently detect ILV defects,particularly in irregularly positioned ILVs,and approximately localize them within clusters,using a walking pattern approach.In the proposed BIST framework,ILVs are grouped according to the probability of fault occurrence,enabling efficient detection of all SAFs and bridging faults(BFs)and most multiple faults within each cluster.This strategy empowers designers to fine-tune fault coverage,localization precision,and test duration to meet specific design requirements.The new BIST method addresses a critical shortcoming of existing solutions by significantly reducing the number of test configurations and overall test time using multiple ILV clusters.The method also enhances efficiency in terms of area and hardware utilization,particularly for larger circuit benchmarks.For instance,in the LU32PEENG benchmark,where ILVs are divided into 64 clusters,the power,area,and hardware overheads are minimized to 0.82%,1.03%,and 1.14%,respectively.展开更多
Security and reliability must be focused on control sys- tems firstly, and fault detection and diagnosis （FDD） is the main theory and technology. Now, there are many positive results in FDD for linear networked cont...Security and reliability must be focused on control sys- tems firstly, and fault detection and diagnosis （FDD） is the main theory and technology. Now, there are many positive results in FDD for linear networked control systems （LNCSs）, but nonlinear networked control systems （NNCSs） are less involved. Based on the T-S fuzzy-modeling theory, NNCSs are modeled and network random time-delays are changed into the unknown bounded uncertain part without changing its structure. Then a fuzzy state observer is designed and an observer-based fault detection approach for an NNCS is presented. The main results are given and the relative theories are proved in detail. Finally, some simulation results are given and demonstrate the proposed method is effective.展开更多
A bilinear fault detection observer is proposed for a class of continuous time singular bilinear systems subject to unknown input disturbance and fault. By singular value decomposition on the original system, a biline...A bilinear fault detection observer is proposed for a class of continuous time singular bilinear systems subject to unknown input disturbance and fault. By singular value decomposition on the original system, a bilinear fault detection observer is proposed for the decomposed system via an algebraic Riccati equation, and the domain of attraction of the state estimation error is estimated. A design procedure is presented to determine the fault detection threshold. A model of flexible joint robot is used to demonstrate the effectiveness of the proposed method.展开更多
This study proposes a scheme for state estimation and,consequently,fault diagnosis in nonlinear systems.Initially,an optimal nonlinear observer is designed for nonlinear systems subject to an actuator or plant fault.B...This study proposes a scheme for state estimation and,consequently,fault diagnosis in nonlinear systems.Initially,an optimal nonlinear observer is designed for nonlinear systems subject to an actuator or plant fault.By utilizing Lyapunov's direct method,the observer is proved to be optimal with respect to a performance function,including the magnitude of the observer gain and the convergence time.The observer gain is obtained by using approximation of Hamilton-Jacobi-Bellman(HJB)equation.The approximation is determined via an online trained neural network(NN).Next a class of affine nonlinear systems is considered which is subject to unknown disturbances in addition to fault signals.In this case,for each fault the original system is transformed to a new form in which the proposed optimal observer can be applied for state estimation and fault detection and isolation(FDI).Simulation results of a singlelink flexible joint robot(SLFJR)electric drive system show the effectiveness of the proposed methodology.展开更多
Single receiver positioning has been widely used as a standard and standalone positioning technique for about 25 years.To detect the slowly growing faults caused by satellite and receiver clocks in single receiver pos...Single receiver positioning has been widely used as a standard and standalone positioning technique for about 25 years.To detect the slowly growing faults caused by satellite and receiver clocks in single receiver positioning,the Autonomous Integrity Monitoring with an Extrapolation method(AIME)was proposed based on the Kalman filter measurement domain.However,AIME was designed with the assumption of there is the same number of visible satellites at each epoch,which limits its application.To address this issue,this paper proposes a state-domain Robust Autonomous Integrity Monitoring with the Extrapolation Method(SRAIME).The slowly growing fault detection statistics is established based on the difference between the estimates of the state propagator and the posterior state estimation in Kalman filtering.Meanwhile,singular value decomposition is adopted to factor the covariance matrix of the difference to increase computational robustness.Besides,the relevant formulas of the proposed method are theoretically derived,and it is proven that the proposed method is suitable for any positioning model based on the Kalman filter.Additionally,the results of two experiments indicate that SRAIME can detect slowly growing faults in single receiver positioning earlier than AIME.展开更多
In this paper,a novel model-based fault detection in the battery management system of an electric vehicle is proposed.Two adaptive observers are designed to detect state-of-charge faults and voltage sensor faults,cons...In this paper,a novel model-based fault detection in the battery management system of an electric vehicle is proposed.Two adaptive observers are designed to detect state-of-charge faults and voltage sensor faults,considering the impact of battery aging.Battery aging primarily affects capacity and resistance,becoming more pronounced in the later stages of a battery lifespan.By incorporating aging effects into our fault diagnosis scheme,our proposed approach prevents false or missed alarms for the aged battery cells.The aging effect of battery,capacity fading and resistance growth,are considered unknown parameters.An adaptive observer is employed to design a fault detector,considering unknown parameters in the battery model.The adaptive observers are designed for two different scenarios:In the first scenario,it is presumed that aging effects remain constant over time due to their slow rate of change.Then,it is assumed that aging effects are time-varying.Therefore,the fault detection scheme can detect faults of new battery cells as well as aged cells.Some simulations have been conducted on a Lithium-ion battery cell and extended to battery pack,to demonstrate the performance of the proposed approach in more real-world scenarios.The results showed that the designed observers can detect faults correctly in a seven years old battery as well as a new one.展开更多
A novel fault detection and identification(FDI)scheme for HVDC(High Voltage Direct Current Transmission)system was presented.It was based on the unique active disturbance rejection concept,where the HVDC system faults...A novel fault detection and identification(FDI)scheme for HVDC(High Voltage Direct Current Transmission)system was presented.It was based on the unique active disturbance rejection concept,where the HVDC system faults were estimated using an extended states observer(ESO).Firstly,the mathematical model of HVDC system was constructed,where the system states and disturbance were treated as an extended state.An augment HVDC system was established by using the extended state in rectify side and converter side,respectively.Then,a fault diagnosis filter was established to diagnose the HVDC system faults via the ESO theory.The evolution of the extended state in the augment HVDC system can reflect the actual system faults and disturbances,which can be used for the fault diagnosis purpose.A novel feature of this approach is that it can simultaneously detect and identify the shape and magnitude of the HVDC faults and disturbance.Finally,different kinds of HVDC faults were simulated to illustrate the feasibility and effectiveness of the proposed ESO based FDI approach.Compared with the neural network based or support vector machine based FDI approach,the ESO based FDI scheme can reduce the fault detection time dramatically and track the actual system fault accurately.What's more important,it needs not do complex online calculations and the training of neural network so that it can be applied into practice.展开更多
基金co-supported by the National Natural Science Foundation of China(Nos.51407144 and 51777169)the Aviation Research Funds(No.20164053029)+1 种基金the Fundamental Research Funds for the Central Universities(Nos.3102017ZY027 and 3102017GX08001)the Young Elite Scientist Sponsorship Program by CAST
文摘Arc fault detection is desperately required in Solid State Power Controllers（SSPC） in addition to their fundamental functions because arcs will provoke growing harm and threat to aircraft safety. Experimental study has been done to obtain the faulted current data. In order to improve the detection speed and accuracy, two fast arc fault detection methods have been proposed in this paper with the analysis of only half cycle data. Both Fast Fourier Transform（FFT） and Wavelet Packets Decomposition（WPD） have been adopted to distinguish arc fault currents from normal operation currents. Analysis results show that Alternating Current（AC） arcs can be effectively and accurately detected with the proposed half cycle data based methods. Moreover,experimental verification results have also been provided.
基金supported partly by the Natural Science Foundation China (70571032).
文摘The influence of random short time-delay to networked control systems （NCS） is changed into an unknown bounded uncertain part. Without changing the structure of the system, an Hoo states observer is designed for NCS with short time-delay. Based on the designed states observer, a robust fault detection approach is proposed for NCS. In addition, an optimization method for the selection of the detection threshold is introduced for better tradeoff between the robustness and the sensitivity. Finally, some simulation results demonstrate that the presented states observer is robust and the fault detection for NCS is effective.
基金This work was supported by the National Natural Science Foundation of China(No.60374024)the Program for Changjiang Scholars andInnovative Research Team in University.
文摘A parametric approach to robust fault detection in linear systems with unknown disturbances is presented.The residual is generated using full-order state observers(FSO).Based on an analytical solution to a type of Sylvester matrix equations,the parameterization of the observer gain matrix is given.In terms of the design degrees of freedom provided by the parametric observer design and a group of introduced parameter vectors,a sufficient and necessary condition for fullorder state observer design with disturbance decoupling is then established.By properly constraining the design parameters according to this proposed condition,the effect of the disturbance on the residual signal is also decoupled,and a simple algorithm is developed.The presented approach offers all the degrees of design freedom.Finally,a numerical example illustrates the effect of the proposed approach.
文摘Rotating systems have many applications in wide-ranging industrial contexts. The breakdown of this equipment results in economic wastes and leads to dangerous situations. To avoid such problems is very important, and it can be done through tools that inform about the existence of faults, as well as, about their progress in time. A review of the modeling process used for rotor-support-structure shows that the finite element method is the maj or method employed. In this paper, with the aid of well defined theoretical models, obtained using the finite element technique, and the state observer method for the identification and location of faults, it is possible to monitor the parameters of a rotor-support-structure system, including the foundation effects. In order to improve safety, these parameters must be supervised in case of the occurrence of failures or faults. The state observers are designed using Linear Matrix Inequalities （LMIs）. Finally, experimental results （using for this a rotation system in the mechanical vibrations laboratory at Ilha Solteira＇s Mechanical Engineering Department） demonstrate the effectiveness of the methodology developed.
文摘Monolithic three-dimensional integrated circuits(M3D ICs)have emerged as an innovative solution to overcome the limitations of traditional 2D scaling,offering improved performance,reduced power consumption,and enhanced functionality.Inter-layer vias(ILVs),crucial components of M3D ICs,provide vertical connectivity between layers but are susceptible to manufacturing and operational defects,such as stuck-at faults(SAFs),shorts,and opens,which can compromise system reliability.These challenges necessitate advanced built-in self-test(BIST)methodologies to ensure robust fault detection and localization while minimizing the testing overhead.In this paper,we introduce a novel BIST architecture tailored to efficiently detect ILV defects,particularly in irregularly positioned ILVs,and approximately localize them within clusters,using a walking pattern approach.In the proposed BIST framework,ILVs are grouped according to the probability of fault occurrence,enabling efficient detection of all SAFs and bridging faults(BFs)and most multiple faults within each cluster.This strategy empowers designers to fine-tune fault coverage,localization precision,and test duration to meet specific design requirements.The new BIST method addresses a critical shortcoming of existing solutions by significantly reducing the number of test configurations and overall test time using multiple ILV clusters.The method also enhances efficiency in terms of area and hardware utilization,particularly for larger circuit benchmarks.For instance,in the LU32PEENG benchmark,where ILVs are divided into 64 clusters,the power,area,and hardware overheads are minimized to 0.82%,1.03%,and 1.14%,respectively.
文摘Security and reliability must be focused on control sys- tems firstly, and fault detection and diagnosis （FDD） is the main theory and technology. Now, there are many positive results in FDD for linear networked control systems （LNCSs）, but nonlinear networked control systems （NNCSs） are less involved. Based on the T-S fuzzy-modeling theory, NNCSs are modeled and network random time-delays are changed into the unknown bounded uncertain part without changing its structure. Then a fuzzy state observer is designed and an observer-based fault detection approach for an NNCS is presented. The main results are given and the relative theories are proved in detail. Finally, some simulation results are given and demonstrate the proposed method is effective.
基金This work was supported in part by National Nature Science Foundation of China (No. 60325311, 60534010, 60572070)the Funds for Creative Research Groups of China (No. 60521003)the Program for Changjiang Scholars and Innovative Research Team in University (No. IRT0421).
文摘A bilinear fault detection observer is proposed for a class of continuous time singular bilinear systems subject to unknown input disturbance and fault. By singular value decomposition on the original system, a bilinear fault detection observer is proposed for the decomposed system via an algebraic Riccati equation, and the domain of attraction of the state estimation error is estimated. A design procedure is presented to determine the fault detection threshold. A model of flexible joint robot is used to demonstrate the effectiveness of the proposed method.
文摘This study proposes a scheme for state estimation and,consequently,fault diagnosis in nonlinear systems.Initially,an optimal nonlinear observer is designed for nonlinear systems subject to an actuator or plant fault.By utilizing Lyapunov's direct method,the observer is proved to be optimal with respect to a performance function,including the magnitude of the observer gain and the convergence time.The observer gain is obtained by using approximation of Hamilton-Jacobi-Bellman(HJB)equation.The approximation is determined via an online trained neural network(NN).Next a class of affine nonlinear systems is considered which is subject to unknown disturbances in addition to fault signals.In this case,for each fault the original system is transformed to a new form in which the proposed optimal observer can be applied for state estimation and fault detection and isolation(FDI).Simulation results of a singlelink flexible joint robot(SLFJR)electric drive system show the effectiveness of the proposed methodology.
基金This work was supported by the Fundamental Research Funds for the Central Universities(No.2019XKQYMS52)the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD).
文摘Single receiver positioning has been widely used as a standard and standalone positioning technique for about 25 years.To detect the slowly growing faults caused by satellite and receiver clocks in single receiver positioning,the Autonomous Integrity Monitoring with an Extrapolation method(AIME)was proposed based on the Kalman filter measurement domain.However,AIME was designed with the assumption of there is the same number of visible satellites at each epoch,which limits its application.To address this issue,this paper proposes a state-domain Robust Autonomous Integrity Monitoring with the Extrapolation Method(SRAIME).The slowly growing fault detection statistics is established based on the difference between the estimates of the state propagator and the posterior state estimation in Kalman filtering.Meanwhile,singular value decomposition is adopted to factor the covariance matrix of the difference to increase computational robustness.Besides,the relevant formulas of the proposed method are theoretically derived,and it is proven that the proposed method is suitable for any positioning model based on the Kalman filter.Additionally,the results of two experiments indicate that SRAIME can detect slowly growing faults in single receiver positioning earlier than AIME.
文摘In this paper,a novel model-based fault detection in the battery management system of an electric vehicle is proposed.Two adaptive observers are designed to detect state-of-charge faults and voltage sensor faults,considering the impact of battery aging.Battery aging primarily affects capacity and resistance,becoming more pronounced in the later stages of a battery lifespan.By incorporating aging effects into our fault diagnosis scheme,our proposed approach prevents false or missed alarms for the aged battery cells.The aging effect of battery,capacity fading and resistance growth,are considered unknown parameters.An adaptive observer is employed to design a fault detector,considering unknown parameters in the battery model.The adaptive observers are designed for two different scenarios:In the first scenario,it is presumed that aging effects remain constant over time due to their slow rate of change.Then,it is assumed that aging effects are time-varying.Therefore,the fault detection scheme can detect faults of new battery cells as well as aged cells.Some simulations have been conducted on a Lithium-ion battery cell and extended to battery pack,to demonstrate the performance of the proposed approach in more real-world scenarios.The results showed that the designed observers can detect faults correctly in a seven years old battery as well as a new one.
基金Project Supported by National Natural Science Foundation of China(60574081).
文摘A novel fault detection and identification(FDI)scheme for HVDC(High Voltage Direct Current Transmission)system was presented.It was based on the unique active disturbance rejection concept,where the HVDC system faults were estimated using an extended states observer(ESO).Firstly,the mathematical model of HVDC system was constructed,where the system states and disturbance were treated as an extended state.An augment HVDC system was established by using the extended state in rectify side and converter side,respectively.Then,a fault diagnosis filter was established to diagnose the HVDC system faults via the ESO theory.The evolution of the extended state in the augment HVDC system can reflect the actual system faults and disturbances,which can be used for the fault diagnosis purpose.A novel feature of this approach is that it can simultaneously detect and identify the shape and magnitude of the HVDC faults and disturbance.Finally,different kinds of HVDC faults were simulated to illustrate the feasibility and effectiveness of the proposed ESO based FDI approach.Compared with the neural network based or support vector machine based FDI approach,the ESO based FDI scheme can reduce the fault detection time dramatically and track the actual system fault accurately.What's more important,it needs not do complex online calculations and the training of neural network so that it can be applied into practice.
