The open-circuit fault is one of the most common faults of the automatic ramming drive system(ARDS),and it can be categorized into the open-phase faults of Permanent Magnet Synchronous Motor(PMSM)and the open-circuit ...The open-circuit fault is one of the most common faults of the automatic ramming drive system(ARDS),and it can be categorized into the open-phase faults of Permanent Magnet Synchronous Motor(PMSM)and the open-circuit faults of Voltage Source Inverter(VSI). The stator current serves as a common indicator for detecting open-circuit faults. Due to the identical changes of the stator current between the open-phase faults in the PMSM and failures of double switches within the same leg of the VSI, this paper utilizes the zero-sequence voltage component as an additional diagnostic criterion to differentiate them.Considering the variable conditions and substantial noise of the ARDS, a novel Multi-resolution Network(Mr Net) is proposed, which can extract multi-resolution perceptual information and enhance robustness to the noise. Meanwhile, a feature weighted layer is introduced to allocate higher weights to characteristics situated near the feature frequency. Both simulation and experiment results validate that the proposed fault diagnosis method can diagnose 25 types of open-circuit faults and achieve more than98.28% diagnostic accuracy. In addition, the experiment results also demonstrate that Mr Net has the capability of diagnosing the fault types accurately under the interference of noise signals(Laplace noise and Gaussian noise).展开更多
The operational readiness test(ORT),like weapon testing before firing,is becoming more and more important for systems used in the field.However,the test requirement of the ORT is distinctive.Specifically,the rule of s...The operational readiness test(ORT),like weapon testing before firing,is becoming more and more important for systems used in the field.However,the test requirement of the ORT is distinctive.Specifically,the rule of selecting test items should be changed in different test turns,and whether there is a fault is more important than where the fault is.The popular dependency matrix(D-matrix)processing algorithms becomes low efficient because they cannot change their optimizing direc-tion and spend unnecessary time on fault localization and isola-tion.To this end,this paper proposes a D-matrix processing algorithm named piecewise heuristic algorithm for D-matrix(PHAD).Its key idea is to use a piecewise function comprised of multiple different functions instead of the commonly used fixed function and switch subfunctions according to the test stage.In this manner,PHAD has the capability of changing optimizing direction,precisely matching the variant test requirements,and generating an efficient test sequence.The experiments on the random matrixes of different sizes and densities prove that the proposed algorithm performs better than the classical algo-rithms in terms of expected test cost(ETC)and other metrics.More generally,the piecewise heuristic function shows a new way to design D-matrix processing algorithm and a more flexi-ble heuristic function to meet more complicated test requirements.展开更多
Fault diagnosis occupies a pivotal position within the domain of machine and equipment management.Existing methods,however,often exhibit limitations in their scope of application,typically focusing on specific types o...Fault diagnosis occupies a pivotal position within the domain of machine and equipment management.Existing methods,however,often exhibit limitations in their scope of application,typically focusing on specific types of signals or faults in individual mechanical components while being constrained by data types and inherent characteristics.To address the limitations of existing methods,we propose a fault diagnosis method based on graph neural networks(GNNs)embedded with multirelationships of intrinsic mode functions(MIMF).The approach introduces a novel graph topological structure constructed from the features of intrinsic mode functions(IMFs)of monitored signals and their multirelationships.Additionally,a graph-level based fault diagnosis network model is designed to enhance feature learning capabilities for graph samples and enable flexible application across diverse signal sources and devices.Experimental validation with datasets including independent vibration signals for gear fault detection,mixed vibration signals for concurrent gear and bearing faults,and pressure signals for hydraulic cylinder leakage characterization demonstrates the model's adaptability and superior diagnostic accuracy across various types of signals and mechanical systems.展开更多
An in-memory storage system provides submillisecond latency and improves the concurrency of user applications by caching data into memory from external storage.Fault tolerance of in-memory storage systems is essential...An in-memory storage system provides submillisecond latency and improves the concurrency of user applications by caching data into memory from external storage.Fault tolerance of in-memory storage systems is essential,as the loss of cached data requires access to data from external storage,which evidently increases the response latency.Typically,replication and erasure code(EC)are two fault-tolerant schemes that pose different trade-offs between access performance and storage usage.To help make the best performance and space trade-off,we design ElasticMem,a hybrid fault-tolerant distributed in-memory storage system that supports elastic redundancy transition to dynamically change the fault-tolerant scheme.ElasticMem exploits a novel EC-oriented replication(EOR)that carefully designs the data placement of replication according to the future data layout of EC to enhance the I/O efficiency of redundancy transition.ElasticMem solves the consistency problem caused by concurrent data accesses via a lightweight table-based scheme combined with data bypassing.It detects correlated read and write requests and serves subsequent read requests with local data.We implement a prototype that realizes ElasticMem based on Memcached.Experiments show that ElasticMem remarkably reduces the time of redundancy transition,the overall latency of correlated concurrent data accesses,and the latency of single data access among them.展开更多
This work proposes the application of an iterative learning model predictive control(ILMPC)approach based on an adaptive fault observer(FOBILMPC)for fault-tolerant control and trajectory tracking in air-breathing hype...This work proposes the application of an iterative learning model predictive control(ILMPC)approach based on an adaptive fault observer(FOBILMPC)for fault-tolerant control and trajectory tracking in air-breathing hypersonic vehicles.In order to increase the control amount,this online control legislation makes use of model predictive control(MPC)that is based on the concept of iterative learning control(ILC).By using offline data to decrease the linearized model’s faults,the strategy may effectively increase the robustness of the control system and guarantee that disturbances can be suppressed.An adaptive fault observer is created based on the suggested ILMPC approach in order to enhance overall fault tolerance by estimating and compensating for actuator disturbance and fault degree.During the derivation process,a linearized model of longitudinal dynamics is established.The suggested ILMPC approach is likely to be used in the design of hypersonic vehicle control systems since numerical simulations have demonstrated that it can decrease tracking error and speed up convergence when compared to the offline controller.展开更多
The ammunition loading system manipulator is susceptible to gear failure due to high-frequency,heavyload reciprocating motions and the absence of protective gear components.After a fault occurs,the distribution of fau...The ammunition loading system manipulator is susceptible to gear failure due to high-frequency,heavyload reciprocating motions and the absence of protective gear components.After a fault occurs,the distribution of fault characteristics under different loads is markedly inconsistent,and data is hard to label,which makes it difficult for the traditional diagnosis method based on single-condition training to generalize to different conditions.To address these issues,the paper proposes a novel transfer discriminant neural network(TDNN)for gear fault diagnosis.Specifically,an optimized joint distribution adaptive mechanism(OJDA)is designed to solve the distribution alignment problem between two domains.To improve the classification effect within the domain and the feature recognition capability for a few labeled data,metric learning is introduced to distinguish features from different fault categories.In addition,TDNN adopts a new pseudo-label training strategy to achieve label replacement by comparing the maximum probability of the pseudo-label with the test result.The proposed TDNN is verified in the experimental data set of the artillery manipulator device,and the diagnosis can achieve 99.5%,significantly outperforming other traditional adaptation methods.展开更多
This research focuses on detecting faults in flight vehicles with unstable subsystems operating asynchronously.By accounting for asynchronous switching,a switched model is established,and filters for fault detection(F...This research focuses on detecting faults in flight vehicles with unstable subsystems operating asynchronously.By accounting for asynchronous switching,a switched model is established,and filters for fault detection(FD)in unstable subsystems are developed.The FD challenge is then transformed into an H∞filtering issue.Utilizing the multiple discontinuous Lyapunov function(MDLF)approach and the mode-dependent average dwell time(MDADT)method,sufficient conditions are derived to ensure stability during both fast and slow switching.Furthermore,the existence and solutions for FD filters are provided through linear matrix inequalities(LMIs).The simulation outcomes demonstrated the excellent performance of the developed method in studied cases.展开更多
This paper presents a fault diagnosis method for process faults and sensor faults in a class of nonlinear uncertain systems.The fault detection and isolation architecture consists of a fault detection estimator and a ...This paper presents a fault diagnosis method for process faults and sensor faults in a class of nonlinear uncertain systems.The fault detection and isolation architecture consists of a fault detection estimator and a bank of adaptive isolation estimators,each corresponding to a particular fault type.Adaptive thresholds for fault detection and isolation are presented.Fault detectability conditions characterizing the class of process faults and sensor faults that are detectable by the presented method are derived.A simulation example of robotic arm is used to illustrate the effectiveness of the fault diagnosis method.展开更多
A fault tolerant control methodology based adaptive sliding mode(ASM) backstepping is proposed for near space vehicle(NSV) attitude control system under engine faults. The proposed scheme combined adaptive backsteppin...A fault tolerant control methodology based adaptive sliding mode(ASM) backstepping is proposed for near space vehicle(NSV) attitude control system under engine faults. The proposed scheme combined adaptive backstepping with the sliding mode control strategy could guarantee the system’s stability and track desired signals under external disturbances and engine faults. Firstly, attitude mode description and the engine faulty model are given. Secondly, a nominal control law is designed.Thirdly, a sliding mode observer is given later in order to estimate both the information of engine faults and external disturbances. An adaptive sliding mode technology based on the previous nominal control law is developed via updating faulty parameters. Finally,analyze the system’s fault-tolerant performance and reliability through experiment simulation, which verifies the proposed design of fault-tolerant control can tolerate engine faults, as well as the strong robustness for external disturbance.展开更多
Since the joint actuator of the space robot executes the control instructions frequently in the harsh space environment,it is prone to the partial loss of control effectiveness(PLCE)fault.An adaptive fault-tolerant co...Since the joint actuator of the space robot executes the control instructions frequently in the harsh space environment,it is prone to the partial loss of control effectiveness(PLCE)fault.An adaptive fault-tolerant control algorithm is designed for a space robot system with the uncertain parameters and the PLCE actuator faults.The mathematical model of the system is established based on the Lagrange method,and the PLCE actuator fault is described as an effectiveness factor.The lower bound of the effectiveness factors and the upper bound of the uncertain parameters are estimated by an adaptive strategy,and the estimated value is fed back to the control algorithm.Compared with the traditional fault-tolerant algorithms,the proposed algorithm does not need to predetermine the lower bound of the effectiveness factor,hence it is more in line with the actual engineering application.It is proved that the algorithm can guarantee the stability of the closed-loop system based on the Lyapunov function method.The numerical simulation results show that the proposed algorithm can not only compensate for the uncertain parameters,but also can tolerate the PLCE actuator faults effectively,which verifies the effectiveness and superiority of the control scheme.展开更多
The open-circuit fault of the power switches in shunt active power filter(SAPF) would exacerbate the harmonic pollution of power grid, and degrade the reliability of the devices and system. A fault diagnosis method is...The open-circuit fault of the power switches in shunt active power filter(SAPF) would exacerbate the harmonic pollution of power grid, and degrade the reliability of the devices and system. A fault diagnosis method is proposed based on reference model and an over-modulation strategy under hardware fault tolerance for SAPF. First, a mathematic model is established for SAPF. Second, the residuals are generated by comparing the outputs of reference model and those of actual model, and open-switch fault is detected and diagnosed by residual evaluation. After that, hardware fault tolerance is performed with the three-phase four-switch(TPFS) topology to isolate the faulty phase. Finally, the over-modulation strategy is proposed to increase the voltage transfer ratio of the TPFS topology. Simulation and experimental results verified the feasibility and effectiveness of the proposed method.展开更多
Security and reliability of inverter are an indispensable part in power electronic system. Faults of inverter are usually caused by switch elements’ operating fault. Taking the inverter with hysteresis current contro...Security and reliability of inverter are an indispensable part in power electronic system. Faults of inverter are usually caused by switch elements’ operating fault. Taking the inverter with hysteresis current control as the research object, a universal open-circuit fault location method which can be applied to multiple control strategies is proposed in the paper. If the switch open-circuit fault happens in inverter, the output phase current will inevitably change, which can be used as a characteristic for diagnosis, combined with the comparison of phase-current direction before and after the fault occurrence, to diagnose and locate the open-circuit fault in a half cycle. Moreover, this method requires neither system control signals nor sensor. The validity, reliability and limitation of the fault location method in the paper are verified and analyzed through dSPACE-based experiment platform.展开更多
Fault prediction technology of running state of electromechanical systems is one of the key technologies that ensure safe and reliable operation of electromechanical equipment in health state. For multiple types of mo...Fault prediction technology of running state of electromechanical systems is one of the key technologies that ensure safe and reliable operation of electromechanical equipment in health state. For multiple types of modern, high-end and key electromechanical equipment, this paper will describe the early faults prediction method for multi-type electromechanical systems, which is favorable for predicting early faults of complex electromechanical systems in non-stationary, nonlinear, variable working conditions and long-time running state; the paper shall introduce the reconfigurable integration technology of series safety monitoring systems based on which the integrated development platform of series safety monitoring systems is built. This platform can adapt to integrated R&D of series safety monitoring systems characterized by high technology, multiple species and low volume. With the help of this platform, series safety monitoring systems were developed, and the Remote Network Security Monitoring Center for Facility Groups was built. Experimental research and engineering applications show that: this new fault prediction method has realized the development trend features extraction of typical electromechanical systems, multi-information fusion, intelligent information decision-making and so on, improving the processing accuracy, relevance and applicability of information; new reconfigurable integration technologies have improved the integration level and R&D efficiency of series safety monitoring systems as well as expanded the scope of application; the series safety monitoring systems developed based on reconfigurable integration platform has already played an important role in many aspects including ensuring safety operation of equipment, stabilizing product quality, optimizing running state, saving energy consumption, reducing environmental pollution, improving working conditions, carrying out scientific maintenance, advancing equipment utilization, saving maintenance charge and enhancing the level of information management.展开更多
A model-based fault tolerant control approach for hybrid linear dynamic systems is proposed in this paper. The proposed method, taking advantage of reliable control, can maintain the performance of the faulty system d...A model-based fault tolerant control approach for hybrid linear dynamic systems is proposed in this paper. The proposed method, taking advantage of reliable control, can maintain the performance of the faulty system during the time delay of fault detection and diagnosis (FDD) and fault accommodation (FA), which can be regarded as the first line of defence against sensor faults. Simulation results of a three-tank system with sensor fault are given to show the efficiency of the method.展开更多
Up to present,the problem of the evaluation of fault diagnosability for nonlinear systems has been investigated by many researchers.However,no attempt has been done to evaluate the diagnosability of multiple faults oc...Up to present,the problem of the evaluation of fault diagnosability for nonlinear systems has been investigated by many researchers.However,no attempt has been done to evaluate the diagnosability of multiple faults occurring simultaneously for nonlinear systems.This paper proposes a method based on differential geometry theories to solve this problem.Then the evaluation of fault diagnosability for affine nonlinear systems with multiple faults occurring simultaneously is achieved.To deal with the effect of control laws on the evaluation results of fault diagnosability,a design scheme of the evaluation of fault diagnosability is proposed.Then the influence of uncertainties on the evaluation results of fault diagnosability for affine nonlinear systems with multiple faults occurring simultaneously is analyzed.The numerical simulation results are obtained to show the effectiveness of the proposed evaluation scheme of fault diagnosability.展开更多
Component failures can cause multi-agent system(MAS)performance degradation and even disasters,which provokes the demand of the fault diagnosis method.A distributed sliding mode observer-based fault diagnosis method f...Component failures can cause multi-agent system(MAS)performance degradation and even disasters,which provokes the demand of the fault diagnosis method.A distributed sliding mode observer-based fault diagnosis method for MAS is developed in presence of actuator and sensor faults.Firstly,the actuator and sensor faults are extended to the system state,and the system is transformed into a descriptor system form.Then,a sliding mode-based distributed unknown input observer is proposed to estimate the extended state.Furthermore,adaptive laws are introduced to adjust the observer parameters.Finally,the effectiveness of the proposed method is demonstrated with numerical simulations.展开更多
基金supported by the Natural Science Foundation of Jiangsu Province (Grant Nos. BK20210347)。
文摘The open-circuit fault is one of the most common faults of the automatic ramming drive system(ARDS),and it can be categorized into the open-phase faults of Permanent Magnet Synchronous Motor(PMSM)and the open-circuit faults of Voltage Source Inverter(VSI). The stator current serves as a common indicator for detecting open-circuit faults. Due to the identical changes of the stator current between the open-phase faults in the PMSM and failures of double switches within the same leg of the VSI, this paper utilizes the zero-sequence voltage component as an additional diagnostic criterion to differentiate them.Considering the variable conditions and substantial noise of the ARDS, a novel Multi-resolution Network(Mr Net) is proposed, which can extract multi-resolution perceptual information and enhance robustness to the noise. Meanwhile, a feature weighted layer is introduced to allocate higher weights to characteristics situated near the feature frequency. Both simulation and experiment results validate that the proposed fault diagnosis method can diagnose 25 types of open-circuit faults and achieve more than98.28% diagnostic accuracy. In addition, the experiment results also demonstrate that Mr Net has the capability of diagnosing the fault types accurately under the interference of noise signals(Laplace noise and Gaussian noise).
文摘The operational readiness test(ORT),like weapon testing before firing,is becoming more and more important for systems used in the field.However,the test requirement of the ORT is distinctive.Specifically,the rule of selecting test items should be changed in different test turns,and whether there is a fault is more important than where the fault is.The popular dependency matrix(D-matrix)processing algorithms becomes low efficient because they cannot change their optimizing direc-tion and spend unnecessary time on fault localization and isola-tion.To this end,this paper proposes a D-matrix processing algorithm named piecewise heuristic algorithm for D-matrix(PHAD).Its key idea is to use a piecewise function comprised of multiple different functions instead of the commonly used fixed function and switch subfunctions according to the test stage.In this manner,PHAD has the capability of changing optimizing direction,precisely matching the variant test requirements,and generating an efficient test sequence.The experiments on the random matrixes of different sizes and densities prove that the proposed algorithm performs better than the classical algo-rithms in terms of expected test cost(ETC)and other metrics.More generally,the piecewise heuristic function shows a new way to design D-matrix processing algorithm and a more flexi-ble heuristic function to meet more complicated test requirements.
文摘Fault diagnosis occupies a pivotal position within the domain of machine and equipment management.Existing methods,however,often exhibit limitations in their scope of application,typically focusing on specific types of signals or faults in individual mechanical components while being constrained by data types and inherent characteristics.To address the limitations of existing methods,we propose a fault diagnosis method based on graph neural networks(GNNs)embedded with multirelationships of intrinsic mode functions(MIMF).The approach introduces a novel graph topological structure constructed from the features of intrinsic mode functions(IMFs)of monitored signals and their multirelationships.Additionally,a graph-level based fault diagnosis network model is designed to enhance feature learning capabilities for graph samples and enable flexible application across diverse signal sources and devices.Experimental validation with datasets including independent vibration signals for gear fault detection,mixed vibration signals for concurrent gear and bearing faults,and pressure signals for hydraulic cylinder leakage characterization demonstrates the model's adaptability and superior diagnostic accuracy across various types of signals and mechanical systems.
基金supported by the Fundamental Research Funds for the Central Universities(WK2150110022)Anhui Provincial Natural Science Foundation(2208085QF189)National Natural Science Foundation of China(62202440).
文摘An in-memory storage system provides submillisecond latency and improves the concurrency of user applications by caching data into memory from external storage.Fault tolerance of in-memory storage systems is essential,as the loss of cached data requires access to data from external storage,which evidently increases the response latency.Typically,replication and erasure code(EC)are two fault-tolerant schemes that pose different trade-offs between access performance and storage usage.To help make the best performance and space trade-off,we design ElasticMem,a hybrid fault-tolerant distributed in-memory storage system that supports elastic redundancy transition to dynamically change the fault-tolerant scheme.ElasticMem exploits a novel EC-oriented replication(EOR)that carefully designs the data placement of replication according to the future data layout of EC to enhance the I/O efficiency of redundancy transition.ElasticMem solves the consistency problem caused by concurrent data accesses via a lightweight table-based scheme combined with data bypassing.It detects correlated read and write requests and serves subsequent read requests with local data.We implement a prototype that realizes ElasticMem based on Memcached.Experiments show that ElasticMem remarkably reduces the time of redundancy transition,the overall latency of correlated concurrent data accesses,and the latency of single data access among them.
基金supported by the National Natural Science Foundation of China(12072090).
文摘This work proposes the application of an iterative learning model predictive control(ILMPC)approach based on an adaptive fault observer(FOBILMPC)for fault-tolerant control and trajectory tracking in air-breathing hypersonic vehicles.In order to increase the control amount,this online control legislation makes use of model predictive control(MPC)that is based on the concept of iterative learning control(ILC).By using offline data to decrease the linearized model’s faults,the strategy may effectively increase the robustness of the control system and guarantee that disturbances can be suppressed.An adaptive fault observer is created based on the suggested ILMPC approach in order to enhance overall fault tolerance by estimating and compensating for actuator disturbance and fault degree.During the derivation process,a linearized model of longitudinal dynamics is established.The suggested ILMPC approach is likely to be used in the design of hypersonic vehicle control systems since numerical simulations have demonstrated that it can decrease tracking error and speed up convergence when compared to the offline controller.
文摘The ammunition loading system manipulator is susceptible to gear failure due to high-frequency,heavyload reciprocating motions and the absence of protective gear components.After a fault occurs,the distribution of fault characteristics under different loads is markedly inconsistent,and data is hard to label,which makes it difficult for the traditional diagnosis method based on single-condition training to generalize to different conditions.To address these issues,the paper proposes a novel transfer discriminant neural network(TDNN)for gear fault diagnosis.Specifically,an optimized joint distribution adaptive mechanism(OJDA)is designed to solve the distribution alignment problem between two domains.To improve the classification effect within the domain and the feature recognition capability for a few labeled data,metric learning is introduced to distinguish features from different fault categories.In addition,TDNN adopts a new pseudo-label training strategy to achieve label replacement by comparing the maximum probability of the pseudo-label with the test result.The proposed TDNN is verified in the experimental data set of the artillery manipulator device,and the diagnosis can achieve 99.5%,significantly outperforming other traditional adaptation methods.
基金the National Natural Science Foundation of China(Grant Nos.62303380,62176214,62101590,62003268)the Aeronautical Science Foundation of China(Grant No.201907053001).
文摘This research focuses on detecting faults in flight vehicles with unstable subsystems operating asynchronously.By accounting for asynchronous switching,a switched model is established,and filters for fault detection(FD)in unstable subsystems are developed.The FD challenge is then transformed into an H∞filtering issue.Utilizing the multiple discontinuous Lyapunov function(MDLF)approach and the mode-dependent average dwell time(MDADT)method,sufficient conditions are derived to ensure stability during both fast and slow switching.Furthermore,the existence and solutions for FD filters are provided through linear matrix inequalities(LMIs).The simulation outcomes demonstrated the excellent performance of the developed method in studied cases.
文摘This paper presents a fault diagnosis method for process faults and sensor faults in a class of nonlinear uncertain systems.The fault detection and isolation architecture consists of a fault detection estimator and a bank of adaptive isolation estimators,each corresponding to a particular fault type.Adaptive thresholds for fault detection and isolation are presented.Fault detectability conditions characterizing the class of process faults and sensor faults that are detectable by the presented method are derived.A simulation example of robotic arm is used to illustrate the effectiveness of the fault diagnosis method.
基金supported by the National Natural Science Foundation of China(6140321061601228+3 种基金61603191)the Natural Science Foundation of Jiangsu(BK20161021)the Nanjing University of Posts and Telecommunications Science Foundation(NY214173)the Open Program of Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing(3DL201607)
文摘A fault tolerant control methodology based adaptive sliding mode(ASM) backstepping is proposed for near space vehicle(NSV) attitude control system under engine faults. The proposed scheme combined adaptive backstepping with the sliding mode control strategy could guarantee the system’s stability and track desired signals under external disturbances and engine faults. Firstly, attitude mode description and the engine faulty model are given. Secondly, a nominal control law is designed.Thirdly, a sliding mode observer is given later in order to estimate both the information of engine faults and external disturbances. An adaptive sliding mode technology based on the previous nominal control law is developed via updating faulty parameters. Finally,analyze the system’s fault-tolerant performance and reliability through experiment simulation, which verifies the proposed design of fault-tolerant control can tolerate engine faults, as well as the strong robustness for external disturbance.
基金supported by the National Natural Science Foundation of China(11372073,11072061)
文摘Since the joint actuator of the space robot executes the control instructions frequently in the harsh space environment,it is prone to the partial loss of control effectiveness(PLCE)fault.An adaptive fault-tolerant control algorithm is designed for a space robot system with the uncertain parameters and the PLCE actuator faults.The mathematical model of the system is established based on the Lagrange method,and the PLCE actuator fault is described as an effectiveness factor.The lower bound of the effectiveness factors and the upper bound of the uncertain parameters are estimated by an adaptive strategy,and the estimated value is fed back to the control algorithm.Compared with the traditional fault-tolerant algorithms,the proposed algorithm does not need to predetermine the lower bound of the effectiveness factor,hence it is more in line with the actual engineering application.It is proved that the algorithm can guarantee the stability of the closed-loop system based on the Lyapunov function method.The numerical simulation results show that the proposed algorithm can not only compensate for the uncertain parameters,but also can tolerate the PLCE actuator faults effectively,which verifies the effectiveness and superiority of the control scheme.
基金Project(2012AA051601)supported by the High-Tech Research and Development Program of China
文摘The open-circuit fault of the power switches in shunt active power filter(SAPF) would exacerbate the harmonic pollution of power grid, and degrade the reliability of the devices and system. A fault diagnosis method is proposed based on reference model and an over-modulation strategy under hardware fault tolerance for SAPF. First, a mathematic model is established for SAPF. Second, the residuals are generated by comparing the outputs of reference model and those of actual model, and open-switch fault is detected and diagnosed by residual evaluation. After that, hardware fault tolerance is performed with the three-phase four-switch(TPFS) topology to isolate the faulty phase. Finally, the over-modulation strategy is proposed to increase the voltage transfer ratio of the TPFS topology. Simulation and experimental results verified the feasibility and effectiveness of the proposed method.
基金Projects(2016YFB1200401,2017YFB1200801)supported by the National Key R&D Program of China
文摘Security and reliability of inverter are an indispensable part in power electronic system. Faults of inverter are usually caused by switch elements’ operating fault. Taking the inverter with hysteresis current control as the research object, a universal open-circuit fault location method which can be applied to multiple control strategies is proposed in the paper. If the switch open-circuit fault happens in inverter, the output phase current will inevitably change, which can be used as a characteristic for diagnosis, combined with the comparison of phase-current direction before and after the fault occurrence, to diagnose and locate the open-circuit fault in a half cycle. Moreover, this method requires neither system control signals nor sensor. The validity, reliability and limitation of the fault location method in the paper are verified and analyzed through dSPACE-based experiment platform.
基金Supported by National Natural Science Fund Project(51275052)Key project supported by Beijing Municipal Natural Science Foundation(3131002)Open topic of Key Laboratory of Key Laboratory of Modern Measurement & Control Technology,Ministry of Education(KF20141123202,KF20111123201)
文摘Fault prediction technology of running state of electromechanical systems is one of the key technologies that ensure safe and reliable operation of electromechanical equipment in health state. For multiple types of modern, high-end and key electromechanical equipment, this paper will describe the early faults prediction method for multi-type electromechanical systems, which is favorable for predicting early faults of complex electromechanical systems in non-stationary, nonlinear, variable working conditions and long-time running state; the paper shall introduce the reconfigurable integration technology of series safety monitoring systems based on which the integrated development platform of series safety monitoring systems is built. This platform can adapt to integrated R&D of series safety monitoring systems characterized by high technology, multiple species and low volume. With the help of this platform, series safety monitoring systems were developed, and the Remote Network Security Monitoring Center for Facility Groups was built. Experimental research and engineering applications show that: this new fault prediction method has realized the development trend features extraction of typical electromechanical systems, multi-information fusion, intelligent information decision-making and so on, improving the processing accuracy, relevance and applicability of information; new reconfigurable integration technologies have improved the integration level and R&D efficiency of series safety monitoring systems as well as expanded the scope of application; the series safety monitoring systems developed based on reconfigurable integration platform has already played an important role in many aspects including ensuring safety operation of equipment, stabilizing product quality, optimizing running state, saving energy consumption, reducing environmental pollution, improving working conditions, carrying out scientific maintenance, advancing equipment utilization, saving maintenance charge and enhancing the level of information management.
基金Supported by National Natural Science Foundation of P.R.China (60574083)Key Laboratory of Process Industry Automation, Ministry of Education of P.R.China (PAL200514)Innovation Scientific Fund of Nanjing University of Aeronautics and Astronautics (Y0508-031)
文摘A model-based fault tolerant control approach for hybrid linear dynamic systems is proposed in this paper. The proposed method, taking advantage of reliable control, can maintain the performance of the faulty system during the time delay of fault detection and diagnosis (FDD) and fault accommodation (FA), which can be regarded as the first line of defence against sensor faults. Simulation results of a three-tank system with sensor fault are given to show the efficiency of the method.
基金the Natural Science Foundation of Fujian Province,China(2019J05024)the Education Department Foundation of Fujian Province,China(JAT170091).
文摘Up to present,the problem of the evaluation of fault diagnosability for nonlinear systems has been investigated by many researchers.However,no attempt has been done to evaluate the diagnosability of multiple faults occurring simultaneously for nonlinear systems.This paper proposes a method based on differential geometry theories to solve this problem.Then the evaluation of fault diagnosability for affine nonlinear systems with multiple faults occurring simultaneously is achieved.To deal with the effect of control laws on the evaluation results of fault diagnosability,a design scheme of the evaluation of fault diagnosability is proposed.Then the influence of uncertainties on the evaluation results of fault diagnosability for affine nonlinear systems with multiple faults occurring simultaneously is analyzed.The numerical simulation results are obtained to show the effectiveness of the proposed evaluation scheme of fault diagnosability.
基金supported by the National Natural Science Foundation of China(62020106003,62003162)111 project(B20007)+1 种基金the Natural Science Foundation of Jiangsu Province of China(BK20200416)the China Postdoctoral Science Foundation(2020TQ0151,2020M681590).
文摘Component failures can cause multi-agent system(MAS)performance degradation and even disasters,which provokes the demand of the fault diagnosis method.A distributed sliding mode observer-based fault diagnosis method for MAS is developed in presence of actuator and sensor faults.Firstly,the actuator and sensor faults are extended to the system state,and the system is transformed into a descriptor system form.Then,a sliding mode-based distributed unknown input observer is proposed to estimate the extended state.Furthermore,adaptive laws are introduced to adjust the observer parameters.Finally,the effectiveness of the proposed method is demonstrated with numerical simulations.
基金supported by the National Nature Science Foundation of China(61304223)the Aeronautical Science Foundation of China(2016ZA52009)the Research Fund for the Doctoral Program of Higher Education of China(20123218120015)
