Some ideas in the development of fault diagnosis system for spacecraft are introduced. Firstly, the architecture of spacecraft fault diagnosis is proposed hierarchically with four diagnosis frames, i.e., system level,...Some ideas in the development of fault diagnosis system for spacecraft are introduced. Firstly, the architecture of spacecraft fault diagnosis is proposed hierarchically with four diagnosis frames, i.e., system level, subsystem level, component level and element level. Secondly, a hierarchical diagnosis model is expressed with four layers, i.e., sensors layer, function layer, behavior layer and structure layer. These layers are used to work together to accomplish the fault alarm, diagnosis and localization. Thirdly, a fault-tree-oriented hybrid knowledge representation based on frame and generalized rule and its relevant reasoning strategy is put forward. Finally, a diagnosis case for spacecraft power system is exemplified combining the above with a powerful expert system development tool G2.展开更多
Effective methods of enhancing the fault-tolerance property are proposed for two kinds of associative memory (AM) neural network (NN) used in high voltage transmission line fault diagnosis. For feedforward NN (FNN),t...Effective methods of enhancing the fault-tolerance property are proposed for two kinds of associative memory (AM) neural network (NN) used in high voltage transmission line fault diagnosis. For feedforward NN (FNN),the conception of 'fake attaction region' is presented to expand the attraction region artificially,and for the feedback Hopfield bidirectional AM NN (BAM-NN),the measure to add redundant neurons is taken to enhance NN's memory capacity and fault-tolerance property. Study results show that the NNs built not only can complete fault diagnosis correctly but also have fairly high fault-tolerance ability for disturbed input information sequence. Moreover FNN is a more convenient and effective method of solving the problem of power system fault diagnosis.展开更多
This paper studied an integrative fault diagnostic system on the power transformer. On-line monitor items were grounded current of iron core, internal partial discharge and oil dissolved gas. Diagnostic techniques wer...This paper studied an integrative fault diagnostic system on the power transformer. On-line monitor items were grounded current of iron core, internal partial discharge and oil dissolved gas. Diagnostic techniques were simple rule-based judgment, fuzzy logistic reasoning and neural network distinguishing. Considering that much faults information was interactional, intellectualized diagnosis was implemented based on integrating the neural network with the expert system. Hologamous integrating strategies were materialized by information-based integrating monitor devices, shared information database on several levels and fusion diagnosis software along thought patterns. The expert system practiced logic thought by logistic reasoning. The neural network realized image thought by model matching. Creative conclusion was educed by their integrating. The diagnosis example showed that the integrative diagnostic system was reasonable and practical.展开更多
It is necessary to develop an automatic fault diagnosis system to avoid a possible nuclear disaster caused by an inaccurate fault diagnosis in the nuclear power plant by the operator. Because Radial Basis Function Neu...It is necessary to develop an automatic fault diagnosis system to avoid a possible nuclear disaster caused by an inaccurate fault diagnosis in the nuclear power plant by the operator. Because Radial Basis Function Neural Network (RBFNN) has the characteristics of optimal approximation and global approximation. The mixed coding of binary system and decimal system is introduced to the structure and parameters of RBFNN, which is trained in course of the genetic optimization. Finally, a fault diagnosis system according to the frequent faults in condensation and feed water system of nuclear power plant is set up. As a result, Genetic-RBF Neural Network (GRBFNN) makes the neural network smaller in size and higher in generalization ability. The diagnosis speed and accuracy are also improved.展开更多
Detection of 2-dimention spark locations by electromagnetic detection method in electrical discharge machining (EDM) is studied. The method, which is applied and investigated, is based on the fact that the release of ...Detection of 2-dimention spark locations by electromagnetic detection method in electrical discharge machining (EDM) is studied. The method, which is applied and investigated, is based on the fact that the release of energy from a spark is transformed into electromagnetic wave around the workpiece. A new sensor system composed of high precision linear Hall components and cubic ferrite is used to detect the intensity of magnetic field. Relation equation between the output of the sensor system and 2-dimention spark locations experiment under a spiculate electrode is introduced, and its diagram of curve is drawn. As a result, the information that can be achieved by detecting spark’s location gives new possibilities for an extended analysis of the EDM-process.展开更多
GP algorithm of correlation dimension computation is ameliorated which overcomes the shortage of traditional one. Improved process of GP algorithm takes the influence of temporal correlative pairs of points on correla...GP algorithm of correlation dimension computation is ameliorated which overcomes the shortage of traditional one. Improved process of GP algorithm takes the influence of temporal correlative pairs of points on correlation dimension into account and promotes the computational efficiency prominently. Iterative SVD method is applied to remove the influence of noise on the result of correlation dimension. The faults of steam flow turbulence and oil film disturbance which occur in 600 MW Steam Turbine Generator are analyzed and whose correlation dimensions are computed. More distinct quantitative index than FFT is gained to distinguish two faults and it’s of little importance to apply correlation dimension to study the influence of various factors on steam flow turbulence fault for nonexistence of convergent floor in correlation integral curve, which presents a new way to learn the operational function of large capacity steam turbine generator and carry out comprehensive condition monitoring.展开更多
Accurate fault detection and diagnosis is important for secure and profitable operation of modern power systems.In this paper,an ensemble of conflict-resolving Fuzzy ARTMAP classifiers,known as Probabilistic Multiple ...Accurate fault detection and diagnosis is important for secure and profitable operation of modern power systems.In this paper,an ensemble of conflict-resolving Fuzzy ARTMAP classifiers,known as Probabilistic Multiple Fuzzy ARTMAP with Dynamic Decay Adjustment(PMFAMDDA),for accurate discrimination between normal and faulty operating conditions of a Circulating Water(CW)system in a power generation plant is proposed.The decisions of PMFAMDDA are reached through a probabilistic plurality voting strategy that is in agreement with the Bayesian theorem.The results of the proposed PMFAMDDA model are compared with those from an ensemble of Probabilistic Multiple Fuzzy ARTMAP(PMFAM)classifiers.The outcomes reveal that PMFAMDDA,in general,outperforms PMFAM in discriminating operating conditions of the CW system.展开更多
A statistical signal processing technique was proposed and verified as independent component analysis(ICA) for fault detection and diagnosis of industrial systems without exact and detailed model.Actually,the aim is t...A statistical signal processing technique was proposed and verified as independent component analysis(ICA) for fault detection and diagnosis of industrial systems without exact and detailed model.Actually,the aim is to utilize system as a black box.The system studied is condenser system of one of MAPNA's power plants.At first,principal component analysis(PCA) approach was applied to reduce the dimensionality of the real acquired data set and to identify the essential and useful ones.Then,the fault sources were diagnosed by ICA technique.The results show that ICA approach is valid and effective for faults detection and diagnosis even in noisy states,and it can distinguish main factors of abnormality among many diverse parts of a power plant's condenser system.This selectivity problem is left unsolved in many plants,because the main factors often become unnoticed by fault expansion through other parts of the plants.展开更多
In paper it introduced a review of modem traction vehicle drive system with induction motor drive system （PMSM with single or dual rotor drive system） or BLDC motor with different configuration of magnetic circuits....In paper it introduced a review of modem traction vehicle drive system with induction motor drive system （PMSM with single or dual rotor drive system） or BLDC motor with different configuration of magnetic circuits. For particular part of drive system proposed a quasi intelligent control system version smart control enables multi criteria predictive control of vehicle work. In the paper presented also a selected diagnostic procedure, enables monitoring exploitation parameters, and prediction of probable failure state. For different vehicle work state realized a simulation models and crash test of exploitations failure models.展开更多
The paper designs the urban-rural power grid dispatching fault diagnosis expert system which acquires fault information by SCADA system of automatic system of urban-rural power grid, and uses artificial intellegence m...The paper designs the urban-rural power grid dispatching fault diagnosis expert system which acquires fault information by SCADA system of automatic system of urban-rural power grid, and uses artificial intellegence method to analyze fault information and make fault diagnosis. The paper implements the core part of the fault expert system the design of knowledge base and fault inference engine.展开更多
For the discrete-time system which is subjected to uncoupled actuator faults and sensor faults simultaneously,a robust fault diagnosis method based on a proportional integral observer (PIO) is presented.The proposed P...For the discrete-time system which is subjected to uncoupled actuator faults and sensor faults simultaneously,a robust fault diagnosis method based on a proportional integral observer (PIO) is presented.The proposed PIO uses an additionally introduced integral term of the output errors to obtain the estimationof actuator faults. Besides, the sensor faults are regarded as the augment states so that the PIO cantrace them. Moreover, the convergence of the PIO is proved. A variable speed wind turbine(VWT) exampleis given to demonstrate the fast convergence and diagnosis precision of the proposed PIO.展开更多
This paper puts forward a new fault diagnosis model based on Petri net.In this new fault diagnosis method,an associated tree is f irst defi ned to describe the logic according to the protections and circuit breakers.A...This paper puts forward a new fault diagnosis model based on Petri net.In this new fault diagnosis method,an associated tree is f irst defi ned to describe the logic according to the protections and circuit breakers.After that a Petri net diagnosis model comes into being and the precise diagnosis of power grid elements can be realized at the same time.The simulation results given in this paper illustrate that this fault diagnosis method can make a rapid diagnosis in complex fault situation and give accurate results to power grid fault diagnosis.展开更多
文摘Some ideas in the development of fault diagnosis system for spacecraft are introduced. Firstly, the architecture of spacecraft fault diagnosis is proposed hierarchically with four diagnosis frames, i.e., system level, subsystem level, component level and element level. Secondly, a hierarchical diagnosis model is expressed with four layers, i.e., sensors layer, function layer, behavior layer and structure layer. These layers are used to work together to accomplish the fault alarm, diagnosis and localization. Thirdly, a fault-tree-oriented hybrid knowledge representation based on frame and generalized rule and its relevant reasoning strategy is put forward. Finally, a diagnosis case for spacecraft power system is exemplified combining the above with a powerful expert system development tool G2.
文摘Effective methods of enhancing the fault-tolerance property are proposed for two kinds of associative memory (AM) neural network (NN) used in high voltage transmission line fault diagnosis. For feedforward NN (FNN),the conception of 'fake attaction region' is presented to expand the attraction region artificially,and for the feedback Hopfield bidirectional AM NN (BAM-NN),the measure to add redundant neurons is taken to enhance NN's memory capacity and fault-tolerance property. Study results show that the NNs built not only can complete fault diagnosis correctly but also have fairly high fault-tolerance ability for disturbed input information sequence. Moreover FNN is a more convenient and effective method of solving the problem of power system fault diagnosis.
文摘This paper studied an integrative fault diagnostic system on the power transformer. On-line monitor items were grounded current of iron core, internal partial discharge and oil dissolved gas. Diagnostic techniques were simple rule-based judgment, fuzzy logistic reasoning and neural network distinguishing. Considering that much faults information was interactional, intellectualized diagnosis was implemented based on integrating the neural network with the expert system. Hologamous integrating strategies were materialized by information-based integrating monitor devices, shared information database on several levels and fusion diagnosis software along thought patterns. The expert system practiced logic thought by logistic reasoning. The neural network realized image thought by model matching. Creative conclusion was educed by their integrating. The diagnosis example showed that the integrative diagnostic system was reasonable and practical.
文摘It is necessary to develop an automatic fault diagnosis system to avoid a possible nuclear disaster caused by an inaccurate fault diagnosis in the nuclear power plant by the operator. Because Radial Basis Function Neural Network (RBFNN) has the characteristics of optimal approximation and global approximation. The mixed coding of binary system and decimal system is introduced to the structure and parameters of RBFNN, which is trained in course of the genetic optimization. Finally, a fault diagnosis system according to the frequent faults in condensation and feed water system of nuclear power plant is set up. As a result, Genetic-RBF Neural Network (GRBFNN) makes the neural network smaller in size and higher in generalization ability. The diagnosis speed and accuracy are also improved.
文摘Detection of 2-dimention spark locations by electromagnetic detection method in electrical discharge machining (EDM) is studied. The method, which is applied and investigated, is based on the fact that the release of energy from a spark is transformed into electromagnetic wave around the workpiece. A new sensor system composed of high precision linear Hall components and cubic ferrite is used to detect the intensity of magnetic field. Relation equation between the output of the sensor system and 2-dimention spark locations experiment under a spiculate electrode is introduced, and its diagram of curve is drawn. As a result, the information that can be achieved by detecting spark’s location gives new possibilities for an extended analysis of the EDM-process.
文摘GP algorithm of correlation dimension computation is ameliorated which overcomes the shortage of traditional one. Improved process of GP algorithm takes the influence of temporal correlative pairs of points on correlation dimension into account and promotes the computational efficiency prominently. Iterative SVD method is applied to remove the influence of noise on the result of correlation dimension. The faults of steam flow turbulence and oil film disturbance which occur in 600 MW Steam Turbine Generator are analyzed and whose correlation dimensions are computed. More distinct quantitative index than FFT is gained to distinguish two faults and it’s of little importance to apply correlation dimension to study the influence of various factors on steam flow turbulence fault for nonexistence of convergent floor in correlation integral curve, which presents a new way to learn the operational function of large capacity steam turbine generator and carry out comprehensive condition monitoring.
基金supported by the Fundamental Research Grant Scheme of Ministry of Higher Education,Malaysia(No.6711195)Multi media University and University of Science Malaysia
文摘Accurate fault detection and diagnosis is important for secure and profitable operation of modern power systems.In this paper,an ensemble of conflict-resolving Fuzzy ARTMAP classifiers,known as Probabilistic Multiple Fuzzy ARTMAP with Dynamic Decay Adjustment(PMFAMDDA),for accurate discrimination between normal and faulty operating conditions of a Circulating Water(CW)system in a power generation plant is proposed.The decisions of PMFAMDDA are reached through a probabilistic plurality voting strategy that is in agreement with the Bayesian theorem.The results of the proposed PMFAMDDA model are compared with those from an ensemble of Probabilistic Multiple Fuzzy ARTMAP(PMFAM)classifiers.The outcomes reveal that PMFAMDDA,in general,outperforms PMFAM in discriminating operating conditions of the CW system.
基金Project(217/s/458)supported by Azarbaijan Shahid Madani University,Iran
文摘A statistical signal processing technique was proposed and verified as independent component analysis(ICA) for fault detection and diagnosis of industrial systems without exact and detailed model.Actually,the aim is to utilize system as a black box.The system studied is condenser system of one of MAPNA's power plants.At first,principal component analysis(PCA) approach was applied to reduce the dimensionality of the real acquired data set and to identify the essential and useful ones.Then,the fault sources were diagnosed by ICA technique.The results show that ICA approach is valid and effective for faults detection and diagnosis even in noisy states,and it can distinguish main factors of abnormality among many diverse parts of a power plant's condenser system.This selectivity problem is left unsolved in many plants,because the main factors often become unnoticed by fault expansion through other parts of the plants.
文摘In paper it introduced a review of modem traction vehicle drive system with induction motor drive system （PMSM with single or dual rotor drive system） or BLDC motor with different configuration of magnetic circuits. For particular part of drive system proposed a quasi intelligent control system version smart control enables multi criteria predictive control of vehicle work. In the paper presented also a selected diagnostic procedure, enables monitoring exploitation parameters, and prediction of probable failure state. For different vehicle work state realized a simulation models and crash test of exploitations failure models.
文摘The paper designs the urban-rural power grid dispatching fault diagnosis expert system which acquires fault information by SCADA system of automatic system of urban-rural power grid, and uses artificial intellegence method to analyze fault information and make fault diagnosis. The paper implements the core part of the fault expert system the design of knowledge base and fault inference engine.
基金Supported by the National Science & Technology Pillar Program in the Eleventh Five-year Plan Period (No. 2007BAF10B00).
文摘For the discrete-time system which is subjected to uncoupled actuator faults and sensor faults simultaneously,a robust fault diagnosis method based on a proportional integral observer (PIO) is presented.The proposed PIO uses an additionally introduced integral term of the output errors to obtain the estimationof actuator faults. Besides, the sensor faults are regarded as the augment states so that the PIO cantrace them. Moreover, the convergence of the PIO is proved. A variable speed wind turbine(VWT) exampleis given to demonstrate the fast convergence and diagnosis precision of the proposed PIO.
文摘This paper puts forward a new fault diagnosis model based on Petri net.In this new fault diagnosis method,an associated tree is f irst defi ned to describe the logic according to the protections and circuit breakers.After that a Petri net diagnosis model comes into being and the precise diagnosis of power grid elements can be realized at the same time.The simulation results given in this paper illustrate that this fault diagnosis method can make a rapid diagnosis in complex fault situation and give accurate results to power grid fault diagnosis.
