A power system fault classification method based on the Hilbert-Huang transformation (HHT) and support vector machine (SVM) is proposed in this paper. According to different types of faults taking place in area and th...A power system fault classification method based on the Hilbert-Huang transformation (HHT) and support vector machine (SVM) is proposed in this paper. According to different types of faults taking place in area and the outer area, this paper uses HHT to extract the instantaneous amplitude and Hilbert marginal spectrum of the current signal. Then a fault classifier consisting of a series of SVM classifiers that are optimized by using cross validation method is constructed. Finally, inputting the feature vector sets that are conversed by the HHT into the fault classifier, the fault type and locate the fault area will be distinguished. The simulation results show that this approach is very effective to classify the fault type especially when the sample is small.展开更多
Nowadays, the elevator has become an indispensable means of indoor transportation in people’s life, but in recent years this kind of traffic tools has caused many casualties because of the gate system fault. In order...Nowadays, the elevator has become an indispensable means of indoor transportation in people’s life, but in recent years this kind of traffic tools has caused many casualties because of the gate system fault. In order to ensure the safe and reliable operation of the elevator, the failure of elevator door system was predicted in this paper. Against the fault type of elevator door system: elevator door opened, excessive vibration when elevator door opened or closed, elevator door did not open or closed when reached the specified level. Three fault types were used as the output of the prediction model. There were 8 reasons for the failure, used them as input. A model based on particle swarm optimization (PSO) and BP neural network was established, using MATLAB to emulation;the results showed that: PSO-BP neural network algorithm was feasible in the fault prediction of the elevator door system.展开更多
The inherent nonlinearities of the rudder servo system(RSS) and the unknown external disturbances bring great challenges to the practical application of fault detection technology. Modeling of whole rudder system is a...The inherent nonlinearities of the rudder servo system(RSS) and the unknown external disturbances bring great challenges to the practical application of fault detection technology. Modeling of whole rudder system is a challenging and difficult task. Quite often, models are too inaccurate, especially in transient stages. In model based fault detection, these inaccuracies might cause wrong actions. An effective approach, which combines nonlinear unknown input observer(NUIO) with an adaptive threshold, is proposed. NUIO can estimate the states of RSS asymptotically without any knowledge of external disturbance. An adaptive threshold is used for decision making which helps to reduce the influence of model uncertainty. Actuator and sensor faults that occur in RSS are considered both by simulation and experimental tests. The observer performance, robustness and fault detection capability are verified. Simulation and experimental results show that the proposed fault detection scheme is efficient and can be used for on-line fault detection.展开更多
This Paper successfully develops the method of Generalized Likelihood Ratio(G.L.R.)in detectingfaults of the system.It has been found very imPOrtant to pay more attention to the validation of measuringdata which must ...This Paper successfully develops the method of Generalized Likelihood Ratio(G.L.R.)in detectingfaults of the system.It has been found very imPOrtant to pay more attention to the validation of measuringdata which must contain richer information relating to the fault.The foil measuringpoints,partial measuring points, single observation and multi-observation for detection of single fault and multi-fault have allbeen considered in our algorithm which basically depends on the theory of G.L.R.,the new concept of calculating residues is also put up as the base of this detecting algorithm. It can not only accurately detect thefaulted branches of the System, but also locate the slanted measures and even determine amplitude of thefault.By simulation with the software MATLAB, the simulation results of some application examples showthat our detection is much better than that by [1]. HOwever, for our method, the precision of sensors shouldbe known and a threshold of confidence for decision should be determined by user.展开更多
The fault system of Liaodong Bay developed extensively under the control of the Tanlu Fault. The fault system can be grouped into strike-slip faults of grade Ⅰ, trunk faults of grade Ⅱand branch faults （induced fau...The fault system of Liaodong Bay developed extensively under the control of the Tanlu Fault. The fault system can be grouped into strike-slip faults of grade Ⅰ, trunk faults of grade Ⅱand branch faults （induced faults） of grade Ⅲ respectively based on its developmental scale. The faults of grade Ⅰ and Ⅱwere deep, early and large while the faults of grade Ⅲwere shallow, late and small. The formation, evolution and distribution features played a significant role in controlling the migration of oil and gas in both horizontal and vertical directions. The fluid transfer in the fault system occurred in the process of faulting. The strike-slip and trunk faults moved actively forming predominant pathways for oil and gas migration. The branch faults, with weak activity, generally controlled the development of traps and were beneficial for the accumulation and preservation of oil and gas. The faults of grade Ⅰ and Ⅱ formed the major migration pathways for oil and gas, but their fault activity rates appeared to vary along their strikes. The zones with a relatively low fault activity rate might be favorable for oil and gas accumulation. When the activities of strike-slip, trunk, and branch faults came to a halt, the fault seal behavior had a vitally important effect on the accumulation of oil and gas. The controlling role of the fault over fluid distribution was further analyzed by calculating the fault activity quantitatively.展开更多
Dynamometer cards are commonly used to analyze down-hole working conditions of pumping systems in actual oil production. Nowadays, the traditional supervised learning methods heavily rely on the classification accurac...Dynamometer cards are commonly used to analyze down-hole working conditions of pumping systems in actual oil production. Nowadays, the traditional supervised learning methods heavily rely on the classification accuracy of the training samples. In order to reduce the errors of manual classification, an automatic clustering algorithm is proposed and applied to diagnose down-hole conditions of pumping systems. The spectral clustering （SC） is a new clustering algorithm, which is suitable for any data distribution. However, it is sensitive to initial cluster centers and scale parameters, and needs to predefine the cluster number. In order to overcome these shortcom- ings, we propose an automatic clustering algorithm, fast black hole-spectral clustering （FBH-SC）. The FBH algo- rithm is used to replace the K-mean method in SC, and a CritC index function is used as the target function to automatically choose the best scale parameter and clus- tering number in the clustering process. Different simulation experiments were designed to define the relationship among scale parameter, clustering number, CritC index value, and clustering accuracy. Finally, an example is given to validate the effectiveness of the proposed algorithm.展开更多
This paper proposes a parity relation based fault estimation for a class of nonlinear systems which can be modelled by Takagi-Sugeno （TS） fuzzy models. The design of a parity relation based residual generator is for...This paper proposes a parity relation based fault estimation for a class of nonlinear systems which can be modelled by Takagi-Sugeno （TS） fuzzy models. The design of a parity relation based residual generator is formulated in terms of a family of linear matrix inequalities （LMIs）. A numerical example is provided to illustrate the effectiveness of the proposed design techniques.展开更多
The networked control system NCS is regarded as a sampled control system withoutput time-variant delay. White noise is considered in the model construction of NCS. By using theKalman filter theory to compute the filte...The networked control system NCS is regarded as a sampled control system withoutput time-variant delay. White noise is considered in the model construction of NCS. By using theKalman filter theory to compute the filter parameters, a Kalman filter is constructed for this NCS.By comparing the output of the filter and the practical system, a residual is generated to diagnoseme sensor faults and the actuator faults. Finally, an example is given to show the feasibility ofthe approach.展开更多
A kind of networked control system is studied; the networked control system with noise disturbance is modeled based on information scheduling and control co-design. Augmented state matrix analysis method is introduced...A kind of networked control system is studied; the networked control system with noise disturbance is modeled based on information scheduling and control co-design. Augmented state matrix analysis method is introduced, and robust fault-tolerant control problem of networked control systems with noise disturbance under actuator failures is studied. The parametric expression of the controller under actuator failures is given. Furthermore, the result is analyzed by simulation tests, which not only satisfies the networked control systems stability, but also decreases the data information number in network channel and makes full use of the network resources.展开更多
An adaptive robust approach for actuator fault-tolerant control of a class of uncertain nonlinear systems is proposed.The two chief ways in which the system performance can degrade following an actuator-fault are unde...An adaptive robust approach for actuator fault-tolerant control of a class of uncertain nonlinear systems is proposed.The two chief ways in which the system performance can degrade following an actuator-fault are undesirable transients and unacceptably large steady-state tracking errors.Adaptive control based schemes can achieve good final tracking accuracy in spite of change in system parameters following an actuator fault,and robust control based designs can achieve guaranteed transient response.However,neither adaptive control nor robust control based fault-tolerant designs can address both the issues associated with actuator faults.In the present work,an adaptive robust fault-tolerant control scheme is claimed to solve both the problems,as it seamlessly integrates adaptive and robust control design techniques.Comparative simulation studies are performed using a nonlinear hypersonic aircraft model to show the effectiveness of the proposed scheme over a robust adaptive control based faulttolerant scheme.展开更多
A new theory- the fuzzy probability logic theory is presented , This theory incorpo- rates the genterally-used fuzzy logic and the traditionally-used probability logic theory in attempt to emulate the rational fault d...A new theory- the fuzzy probability logic theory is presented , This theory incorpo- rates the genterally-used fuzzy logic and the traditionally-used probability logic theory in attempt to emulate the rational fault diagnosis under uncertainty. According to the theory , an inference model , named as FSL , is thus designed to be devoted to the building of a fault diagnosis expert system for rotating machinery (ROSLES) . The system is put into operation on a vibration simula- tor stand for 300 MW turbine generator set ( 1 : 1 0) and satisfactory results are gained.展开更多
Based on the fuzzy expert system fault diagnosis theory, the knowledge base architecture and inference engine algorithm are put forward for avionic device fault diagnosis. The knowledge base is constructed by fault qu...Based on the fuzzy expert system fault diagnosis theory, the knowledge base architecture and inference engine algorithm are put forward for avionic device fault diagnosis. The knowledge base is constructed by fault query network, of which the basic ele- ment is the test-diagnosis fault unit. Every underlying fault cause＇s membership degree is calculated using fuzzy product inference algorithm, and the fault answer best selection algorithm is developed, to which the deep knowledge is applied. Using some examples the proposed algorithm is analyzed for its capability of synthesis diagnosis and its improvement compared to greater membership degree first principle.展开更多
Focusing on the networked control system with long time-delays and data packet dropout,the problem of observerbased fault detection of the system is studied.According to conditions of data arrival of the controller,th...Focusing on the networked control system with long time-delays and data packet dropout,the problem of observerbased fault detection of the system is studied.According to conditions of data arrival of the controller,the state observers of the system are designed to detect faults when they occur in the system.When the system is normal,the observers system is modeled as an uncertain switched system.Based on the model,stability condition of the whole system is given.When conditions are satisfied,the system is asymptotically stable.When a fault occurs,the observers residual can change rapidly to detect the fault.A numerical example shows the effectiveness of the proposed method.展开更多
A class of unknown nonlinear systems subject to uncertain actuator faults and external disturbances will be studied in this paper with the help of fuzzy approximation theory. Using backstepping technique, a novel adap...A class of unknown nonlinear systems subject to uncertain actuator faults and external disturbances will be studied in this paper with the help of fuzzy approximation theory. Using backstepping technique, a novel adaptive fuzzy control approach is proposed to accommodate the uncertain actuator faults during operation and deal with the external disturbances though the systems cannot be linearized by feedback. The considered faults are modeled as both loss of effectiveness and lock-in-place （stuck at some unknown place）. It is proved that the proposed control scheme can guarantee all signals of the closed-loop system to be semi-globally uniformly ultimately bounded and the tracking error between the system output and the reference signal converge to a small neighborhood of zero, though the nonlinear functions of the controlled system as well as the actuator faults and the external disturbances are all unknown. Simulation results demonstrate the effectiveness of the control approach.展开更多
A kind of networked control system with network-induced delay and packet dropout, modeled on asynchronous dynamical systems was tested, and the integrity design of the networked control system with sensors failures an...A kind of networked control system with network-induced delay and packet dropout, modeled on asynchronous dynamical systems was tested, and the integrity design of the networked control system with sensors failures and actuators failures was analyzed using hybrid systems technique based on the robust fault-tolerant control theory. The parametric expression of controller is given based on the feasible solution of linear matrix inequality. The simulation results are provided on the basis of detailed theoretical analysis, which further demonstrate the validity of the proposed schema.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
Aiming at a class of nonlinear systems that contains faults, a novel iterative learning scheme is applied to fault detec- tion, and a novel algorithm of fault detection and estimation is proposed. This algorithm first...Aiming at a class of nonlinear systems that contains faults, a novel iterative learning scheme is applied to fault detec- tion, and a novel algorithm of fault detection and estimation is proposed. This algorithm first constructs residual signals by the output of the practical system and the output of the designed fault tracking estimator, and then uses the residuals and the difference- value signal of the adjacent two residuals to gradually revise the introduced virtual faults, which can cause the virtual faults to close to the practical faults in systems, thereby achieving the goal of fault detection for systems. This algorithm not only makes full use of the existing valid information of systems and has a faster tracking con- vergent speed than the proportional-type （P-type） algorithm, but also calculates more simply than the proportional-derivative-type （PD-type） algorithm and avoids the unstable effects of differential operations in the system. The final simulation results prove the validity of the proposed algorithm.展开更多
Quantized fault detection for sensor/actuator faults of networked control systems （NCSs） with time delays both in the sensor-to-controller channel and controller-to-actuator channel is concerned in this paper. A fau...Quantized fault detection for sensor/actuator faults of networked control systems （NCSs） with time delays both in the sensor-to-controller channel and controller-to-actuator channel is concerned in this paper. A fault model is set up based on the possible cases of sensor/atuator faults. Then, the model predictive control is used to compensate the time delay. When the sensors and actuators are healthy, an H stability criterion of the state predictive observer is obtained in terms of linear matrix inequality. A new threshold computational method that conforms to the actual situation is proposed. Then, the thresholds of the false alarm rate （FAR） and miss detection rate （MDR） are presented by using our proposed method, which are also compared with the ones given in the existin~ literatures. Finally, some numerical simulations are shown to demonstrate the effectiveness of the proposed method.展开更多
The historical records of mechanical fault contain great amount of important information which is useful to identify the similar fault.The current fault diagnosis methods using historical records are inefficient to de...The historical records of mechanical fault contain great amount of important information which is useful to identify the similar fault.The current fault diagnosis methods using historical records are inefficient to deal with intuitive application and multicomponent multiphase fault diagnosis.Towards the problem,the rapid and intelligent fault diagnosis method based on system-phenomenon-fault （SPF） tree is proposed.The method begins with the physical system of the fault system,conceives the fault causes as leaves,the fault causes as leaves and the frequentness of fault as the interrelationship,and finally forms the fault tree with structural relationship of administrative subordination and flexible multi-granularity components.Firstly,the forming method of SPF tree is discussed;Secondly some basic definitions as synonymous branch,the tough degree of the branch,the dominant leaf,and the virtual branch are defined;and then,the performances including the merger of the dominant branches keeping dominant,the merger of the synonymous branches keeping dominant were proved.Furthermore,the merging,optimizing and calculating of virtual branch of SPF tree are proposed,the self-learning mechanism including the procedure and the related parameter calculation is presented,and the fault searching method and main fault statistics calculation are also presented based on SPF tree.Finally,the method is applied in the fault diagnosis of the certain type of embedded terminal to demonstrate fault information searching in the condition of the synonymous branch,the virtual branch merging and visual presentation of search results.The application shows that the proposed method is effective to narrow down the scope of searching fault and reduce the difficulty of computing.The proposed method is a new way to resolve the intelligent fault diagnosis problem of complex systems by organizing the disordering fault records and providing intuitive expression and intelligent computing capabilities.展开更多
文摘A power system fault classification method based on the Hilbert-Huang transformation (HHT) and support vector machine (SVM) is proposed in this paper. According to different types of faults taking place in area and the outer area, this paper uses HHT to extract the instantaneous amplitude and Hilbert marginal spectrum of the current signal. Then a fault classifier consisting of a series of SVM classifiers that are optimized by using cross validation method is constructed. Finally, inputting the feature vector sets that are conversed by the HHT into the fault classifier, the fault type and locate the fault area will be distinguished. The simulation results show that this approach is very effective to classify the fault type especially when the sample is small.
文摘Nowadays, the elevator has become an indispensable means of indoor transportation in people’s life, but in recent years this kind of traffic tools has caused many casualties because of the gate system fault. In order to ensure the safe and reliable operation of the elevator, the failure of elevator door system was predicted in this paper. Against the fault type of elevator door system: elevator door opened, excessive vibration when elevator door opened or closed, elevator door did not open or closed when reached the specified level. Three fault types were used as the output of the prediction model. There were 8 reasons for the failure, used them as input. A model based on particle swarm optimization (PSO) and BP neural network was established, using MATLAB to emulation;the results showed that: PSO-BP neural network algorithm was feasible in the fault prediction of the elevator door system.
基金Project(51221004)supported by the Science Fund for Creative Research Groups of National Natural Science Foundation of ChinaProject(51175453)supported by the National Natural Science Foundation of China
文摘The inherent nonlinearities of the rudder servo system(RSS) and the unknown external disturbances bring great challenges to the practical application of fault detection technology. Modeling of whole rudder system is a challenging and difficult task. Quite often, models are too inaccurate, especially in transient stages. In model based fault detection, these inaccuracies might cause wrong actions. An effective approach, which combines nonlinear unknown input observer(NUIO) with an adaptive threshold, is proposed. NUIO can estimate the states of RSS asymptotically without any knowledge of external disturbance. An adaptive threshold is used for decision making which helps to reduce the influence of model uncertainty. Actuator and sensor faults that occur in RSS are considered both by simulation and experimental tests. The observer performance, robustness and fault detection capability are verified. Simulation and experimental results show that the proposed fault detection scheme is efficient and can be used for on-line fault detection.
文摘This Paper successfully develops the method of Generalized Likelihood Ratio(G.L.R.)in detectingfaults of the system.It has been found very imPOrtant to pay more attention to the validation of measuringdata which must contain richer information relating to the fault.The foil measuringpoints,partial measuring points, single observation and multi-observation for detection of single fault and multi-fault have allbeen considered in our algorithm which basically depends on the theory of G.L.R.,the new concept of calculating residues is also put up as the base of this detecting algorithm. It can not only accurately detect thefaulted branches of the System, but also locate the slanted measures and even determine amplitude of thefault.By simulation with the software MATLAB, the simulation results of some application examples showthat our detection is much better than that by [1]. HOwever, for our method, the precision of sensors shouldbe known and a threshold of confidence for decision should be determined by user.
文摘The fault system of Liaodong Bay developed extensively under the control of the Tanlu Fault. The fault system can be grouped into strike-slip faults of grade Ⅰ, trunk faults of grade Ⅱand branch faults （induced faults） of grade Ⅲ respectively based on its developmental scale. The faults of grade Ⅰ and Ⅱwere deep, early and large while the faults of grade Ⅲwere shallow, late and small. The formation, evolution and distribution features played a significant role in controlling the migration of oil and gas in both horizontal and vertical directions. The fluid transfer in the fault system occurred in the process of faulting. The strike-slip and trunk faults moved actively forming predominant pathways for oil and gas migration. The branch faults, with weak activity, generally controlled the development of traps and were beneficial for the accumulation and preservation of oil and gas. The faults of grade Ⅰ and Ⅱ formed the major migration pathways for oil and gas, but their fault activity rates appeared to vary along their strikes. The zones with a relatively low fault activity rate might be favorable for oil and gas accumulation. When the activities of strike-slip, trunk, and branch faults came to a halt, the fault seal behavior had a vitally important effect on the accumulation of oil and gas. The controlling role of the fault over fluid distribution was further analyzed by calculating the fault activity quantitatively.
基金the National Natural Science Foundation of China (Grant No. 61403040)
文摘Dynamometer cards are commonly used to analyze down-hole working conditions of pumping systems in actual oil production. Nowadays, the traditional supervised learning methods heavily rely on the classification accuracy of the training samples. In order to reduce the errors of manual classification, an automatic clustering algorithm is proposed and applied to diagnose down-hole conditions of pumping systems. The spectral clustering （SC） is a new clustering algorithm, which is suitable for any data distribution. However, it is sensitive to initial cluster centers and scale parameters, and needs to predefine the cluster number. In order to overcome these shortcom- ings, we propose an automatic clustering algorithm, fast black hole-spectral clustering （FBH-SC）. The FBH algo- rithm is used to replace the K-mean method in SC, and a CritC index function is used as the target function to automatically choose the best scale parameter and clus- tering number in the clustering process. Different simulation experiments were designed to define the relationship among scale parameter, clustering number, CritC index value, and clustering accuracy. Finally, an example is given to validate the effectiveness of the proposed algorithm.
基金This work was supported by the Alexander von Humboldt Foundation.
文摘This paper proposes a parity relation based fault estimation for a class of nonlinear systems which can be modelled by Takagi-Sugeno （TS） fuzzy models. The design of a parity relation based residual generator is formulated in terms of a family of linear matrix inequalities （LMIs）. A numerical example is provided to illustrate the effectiveness of the proposed design techniques.
文摘The networked control system NCS is regarded as a sampled control system withoutput time-variant delay. White noise is considered in the model construction of NCS. By using theKalman filter theory to compute the filter parameters, a Kalman filter is constructed for this NCS.By comparing the output of the filter and the practical system, a residual is generated to diagnoseme sensor faults and the actuator faults. Finally, an example is given to show the feasibility ofthe approach.
基金Hohai University Startup Outlay for Doctor Scientific Research (2084/40601136)
文摘A kind of networked control system is studied; the networked control system with noise disturbance is modeled based on information scheduling and control co-design. Augmented state matrix analysis method is introduced, and robust fault-tolerant control problem of networked control systems with noise disturbance under actuator failures is studied. The parametric expression of the controller under actuator failures is given. Furthermore, the result is analyzed by simulation tests, which not only satisfies the networked control systems stability, but also decreases the data information number in network channel and makes full use of the network resources.
基金supported by the US National Science Foundation (CMMI-1052872)the Ministry of Education of China
文摘An adaptive robust approach for actuator fault-tolerant control of a class of uncertain nonlinear systems is proposed.The two chief ways in which the system performance can degrade following an actuator-fault are undesirable transients and unacceptably large steady-state tracking errors.Adaptive control based schemes can achieve good final tracking accuracy in spite of change in system parameters following an actuator fault,and robust control based designs can achieve guaranteed transient response.However,neither adaptive control nor robust control based fault-tolerant designs can address both the issues associated with actuator faults.In the present work,an adaptive robust fault-tolerant control scheme is claimed to solve both the problems,as it seamlessly integrates adaptive and robust control design techniques.Comparative simulation studies are performed using a nonlinear hypersonic aircraft model to show the effectiveness of the proposed scheme over a robust adaptive control based faulttolerant scheme.
文摘A new theory- the fuzzy probability logic theory is presented , This theory incorpo- rates the genterally-used fuzzy logic and the traditionally-used probability logic theory in attempt to emulate the rational fault diagnosis under uncertainty. According to the theory , an inference model , named as FSL , is thus designed to be devoted to the building of a fault diagnosis expert system for rotating machinery (ROSLES) . The system is put into operation on a vibration simula- tor stand for 300 MW turbine generator set ( 1 : 1 0) and satisfactory results are gained.
基金The 11th Five-year National Defense Preliminary Research Projects (B0520060455)
文摘Based on the fuzzy expert system fault diagnosis theory, the knowledge base architecture and inference engine algorithm are put forward for avionic device fault diagnosis. The knowledge base is constructed by fault query network, of which the basic ele- ment is the test-diagnosis fault unit. Every underlying fault cause＇s membership degree is calculated using fuzzy product inference algorithm, and the fault answer best selection algorithm is developed, to which the deep knowledge is applied. Using some examples the proposed algorithm is analyzed for its capability of synthesis diagnosis and its improvement compared to greater membership degree first principle.
基金supported by the Natural Science Foundation of Jiangsu Province (BK2006202)
文摘Focusing on the networked control system with long time-delays and data packet dropout,the problem of observerbased fault detection of the system is studied.According to conditions of data arrival of the controller,the state observers of the system are designed to detect faults when they occur in the system.When the system is normal,the observers system is modeled as an uncertain switched system.Based on the model,stability condition of the whole system is given.When conditions are satisfied,the system is asymptotically stable.When a fault occurs,the observers residual can change rapidly to detect the fault.A numerical example shows the effectiveness of the proposed method.
基金supported by the Funds for Creative Research Groups of China (No.60821063)the State Key Program of National Natural Science of China (No.60534010)+3 种基金the National 973 Program of China (No.2009CB320604)the Funds of National Science of China (No.60674021)the 111 Project (B08015)the Funds of PhD program of MOE,China (No.20060145019)
文摘A class of unknown nonlinear systems subject to uncertain actuator faults and external disturbances will be studied in this paper with the help of fuzzy approximation theory. Using backstepping technique, a novel adaptive fuzzy control approach is proposed to accommodate the uncertain actuator faults during operation and deal with the external disturbances though the systems cannot be linearized by feedback. The considered faults are modeled as both loss of effectiveness and lock-in-place （stuck at some unknown place）. It is proved that the proposed control scheme can guarantee all signals of the closed-loop system to be semi-globally uniformly ultimately bounded and the tracking error between the system output and the reference signal converge to a small neighborhood of zero, though the nonlinear functions of the controlled system as well as the actuator faults and the external disturbances are all unknown. Simulation results demonstrate the effectiveness of the control approach.
基金This project was supported by the National Natural Science Foundation of China (60274014)Doctor Foundation of China Education Ministry (20020487006).
文摘A kind of networked control system with network-induced delay and packet dropout, modeled on asynchronous dynamical systems was tested, and the integrity design of the networked control system with sensors failures and actuators failures was analyzed using hybrid systems technique based on the robust fault-tolerant control theory. The parametric expression of controller is given based on the feasible solution of linear matrix inequality. The simulation results are provided on the basis of detailed theoretical analysis, which further demonstrate the validity of the proposed schema.
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 the National Natural Science Foundation of China (61100103)
文摘Aiming at a class of nonlinear systems that contains faults, a novel iterative learning scheme is applied to fault detec- tion, and a novel algorithm of fault detection and estimation is proposed. This algorithm first constructs residual signals by the output of the practical system and the output of the designed fault tracking estimator, and then uses the residuals and the difference- value signal of the adjacent two residuals to gradually revise the introduced virtual faults, which can cause the virtual faults to close to the practical faults in systems, thereby achieving the goal of fault detection for systems. This algorithm not only makes full use of the existing valid information of systems and has a faster tracking con- vergent speed than the proportional-type （P-type） algorithm, but also calculates more simply than the proportional-derivative-type （PD-type） algorithm and avoids the unstable effects of differential operations in the system. The final simulation results prove the validity of the proposed algorithm.
基金supported by National Natural Science Foundation of China(No.61074065)Natural Science Foundation of Hebei Province(No.F2012203184)Specialized Research Fund for the Doctoral Program of Higher Education of China(No.20111333120009)
文摘Quantized fault detection for sensor/actuator faults of networked control systems （NCSs） with time delays both in the sensor-to-controller channel and controller-to-actuator channel is concerned in this paper. A fault model is set up based on the possible cases of sensor/atuator faults. Then, the model predictive control is used to compensate the time delay. When the sensors and actuators are healthy, an H stability criterion of the state predictive observer is obtained in terms of linear matrix inequality. A new threshold computational method that conforms to the actual situation is proposed. Then, the thresholds of the false alarm rate （FAR） and miss detection rate （MDR） are presented by using our proposed method, which are also compared with the ones given in the existin~ literatures. Finally, some numerical simulations are shown to demonstrate the effectiveness of the proposed method.
基金supported by National Hi-tech Research and Development Program of China (863 key Program,Grant No.2007AA040701)Chongqing Municipal Natural Science Foundation Project of China (Grant No. CSTC2010BB4295)+2 种基金Research Fund for the Doctoral Program of Higher Education of China (Grant No.20100191120004)Fundamental Research Funds for the Central Universities of China (Grant No. CDJXS11111136)Research Foundation of Chongqing University of Science and Technology,China(Grant No. CK2010Z10)
文摘The historical records of mechanical fault contain great amount of important information which is useful to identify the similar fault.The current fault diagnosis methods using historical records are inefficient to deal with intuitive application and multicomponent multiphase fault diagnosis.Towards the problem,the rapid and intelligent fault diagnosis method based on system-phenomenon-fault （SPF） tree is proposed.The method begins with the physical system of the fault system,conceives the fault causes as leaves,the fault causes as leaves and the frequentness of fault as the interrelationship,and finally forms the fault tree with structural relationship of administrative subordination and flexible multi-granularity components.Firstly,the forming method of SPF tree is discussed;Secondly some basic definitions as synonymous branch,the tough degree of the branch,the dominant leaf,and the virtual branch are defined;and then,the performances including the merger of the dominant branches keeping dominant,the merger of the synonymous branches keeping dominant were proved.Furthermore,the merging,optimizing and calculating of virtual branch of SPF tree are proposed,the self-learning mechanism including the procedure and the related parameter calculation is presented,and the fault searching method and main fault statistics calculation are also presented based on SPF tree.Finally,the method is applied in the fault diagnosis of the certain type of embedded terminal to demonstrate fault information searching in the condition of the synonymous branch,the virtual branch merging and visual presentation of search results.The application shows that the proposed method is effective to narrow down the scope of searching fault and reduce the difficulty of computing.The proposed method is a new way to resolve the intelligent fault diagnosis problem of complex systems by organizing the disordering fault records and providing intuitive expression and intelligent computing capabilities.
