This paper focuses on electrical fault diagnosis and operation and maintenance technology in property service electromechanical engineering.It details core diagnostic methods,application-oriented tools,predictive main...This paper focuses on electrical fault diagnosis and operation and maintenance technology in property service electromechanical engineering.It details core diagnostic methods,application-oriented tools,predictive maintenance frameworks,and enhanced maintenance planning.It also explores wireless sensor networks,big data analytics,and design-phase applications.Case studies in construction and operation phases are presented.Challenges like legacy system retrofitting are noted,and future potential in quantum sensing and edge AI is discussed.展开更多
The power infrastructure of the power system is massive in size and dispersed throughout the system.Therefore,how to protect the information security in the operation and maintenance of power equipment is a difficult ...The power infrastructure of the power system is massive in size and dispersed throughout the system.Therefore,how to protect the information security in the operation and maintenance of power equipment is a difficult problem.This paper proposes an improved time-stamped blockchain technology biometric fuzzy feature for electrical equipment maintenance.Compared with previous blockchain transactions,the time-stamped fuzzy biometric signature proposed in this paper overcomes the difficulty that the key is easy to be stolen by hackers and can protect the security of information during operation and maintenance.Finally,the effectiveness of the proposed method is verified by experiments.展开更多
VFDs （variable frequency drives） are an integral part of many industrial plants and stations. Reliable operation and maintenance of these drives is vital to ensure sustained plant operation and availability. Underst...VFDs （variable frequency drives） are an integral part of many industrial plants and stations. Reliable operation and maintenance of these drives is vital to ensure sustained plant operation and availability. Understanding of the principles of operation of VFD systems as well as knowledge about their required operating environment is necessary for all operating personnel. Many times the operating personnel do not get involved with different technical issues until a complete failure has occurred. Hence, the awareness of the most dominant failure causes has a significant impact on assisting operators to avoid catastrophic failures and tremendous economic losses due to VFD shutdown. Proper plant design, accurate monitoring and data logging, following manufacturer preventive maintenance schedule, and choosing qualified team of operators can be the key to an efficient operation and a long lifetime for any VFD system. In this paper, we have analyzed the electrical and non-electrical causes of VFD failures based on a case study of a typical medium voltage VFD pumping station. Finally, recommendations are given from field analysis and observations.展开更多
In order to study intelligent fault diagnosis methods based on fuzzy neural network (NN) expert system and build up intelligent fault diagnosis for a type of missile weapon system, the concrete implementation of a fuz...In order to study intelligent fault diagnosis methods based on fuzzy neural network (NN) expert system and build up intelligent fault diagnosis for a type of missile weapon system, the concrete implementation of a fuzzy NN fault diagnosis expert system is given in this paper. Based on thorough research of knowledge presentation, the intelligent fault diagnosis system is implemented with artificial intelligence for a large-scale missile weapon equipment. The method is an effective way to perform fuzzy fault diagnosis. Moreover, it provides a new way of the fault diagnosis for large-scale missile weapon equipment.展开更多
With the development of large-scale complicated modern power systems, the requirement for the associated protection scheme tends to be more stringent and its combination more complex. However, it is very difficult to ...With the development of large-scale complicated modern power systems, the requirement for the associated protection scheme tends to be more stringent and its combination more complex. However, it is very difficult to figure out the factors of failure of such systems. This paper proposes a Petri net model of a transmission line protection relaying system, including three types of relays as well as an automatic reclosing device, and shows how to diagnose serial failure of the system by analyzing invariant sets of the model. Furthermore, it gives four basic types of failure sequences and its execution is much more intuitive and effective than the traditional method.展开更多
To diagnose the aeroengine faults accurately,the supervised Kohonen(S-Kohonen)network is proposed for fault diagnosis.Via adding the output layer behind competitive layer,the network was modified from the unsupervised...To diagnose the aeroengine faults accurately,the supervised Kohonen(S-Kohonen)network is proposed for fault diagnosis.Via adding the output layer behind competitive layer,the network was modified from the unsupervised structure to the supervised structure.Meanwhile,the hybrid particle swarm optimization(H-PSO)was used to optimize the connection weights,after using adaptive inheritance mode(AIM)based on the elite strategy,and adaptive detecting response mechanism(ADRM),HPSO could guide the particles adaptively jumping out of the local solution space,and ensure obtaining the global optimal solution with higher probability.So the optimized S-Kohonen network could overcome the problems of non-identifiability for recognizing the unknown samples,and the non-uniqueness for classification results existing in traditional Kohonen(T-Kohonen)network.The comparison study on the GE90 engine borescope image texture feature recognition is carried out,the research results show that:the optimized S-Kohonen network has a strong ability of practical application in the classification fault diagnosis;the classification accuracy is higher than the common neural network model.展开更多
the power network fault detection system can only analyze all kinds of fault signal in stationary sequence： the internal grid and external disturbance presents degeneration, tiny, signal intensity changes randomly fl...the power network fault detection system can only analyze all kinds of fault signal in stationary sequence： the internal grid and external disturbance presents degeneration, tiny, signal intensity changes randomly fluctuate, that will cause the system to detect the fault isolation ability of confusion and small fault signal is not strong; The article propose a method of power network fault detection for based on GSM, Through the underlying sensing equipment acquisition abnormal information of current, voltage power in the network and GSM networking scheme can filter the interference factors in extraction of fault information from and attribute value. The embedded gateway take STM32 chip as the core to monitoring data processing, to achieve a unified data management and user remote access, realizing method of system software are given, to construct the monitor management information platform. The actual test system show that, identification diagnosis ability of fault signal separation ability and small signal increases 17%, also meet the requirements.展开更多
In the contemporary energy landscape,the transition from traditional power grids to smart grids is being increasingly facilitated by the real-time monitoring,protection,and control capabilities provided by wide-area m...In the contemporary energy landscape,the transition from traditional power grids to smart grids is being increasingly facilitated by the real-time monitoring,protection,and control capabilities provided by wide-area measurement systems.The core of this evolution is the synchrophasor technology,which provides time-synchronized phasor measurements(an essential component for the successful implementation of smart grids).These phasor measurements are acquired through advanced,rapid,time-stamped devices known as phasor measurement units(PMUs),which play a pivotal role in enhancing grid reliability and efficiency.PMUs providehigh accuracy and precision in capturing electric phasors.This advancement has significantly contributed to the reliability of power systems.The data obtained from the PMUs can be applied across a diverse range of contexts and categorized according to their time criticality requirements.Furthermore,the applications can be classified according to their operational foci.A comprehensive review of the pivotal role of PMUs within the context of smart grid systems is presented.It systematically addresses the following key areas:the significance of real-time monitoring and control facilitated by PMUs in smart grids,contribution of PMUs to enhanced situational awareness,utilization of PMU data for state estimation applications,and critical function of PMUs in accurately identifying faults and their locations within the smart grid infrastructure.Additionally,PMU data management is explored.The focus here is on the processes of data acquisition and transmission enabled by PMUs in smart grids and the relevant communication technologies and protocols employed.This study aims to highlight the integral role of PMUs in optimizing the performance and reliability of smart grid networks.展开更多
Electrical insulation faults produce partial discharges(PD),which can be analysed to identify specific types of defects.PD clustering is a widely used method to identify PD sources,although its success depends largely...Electrical insulation faults produce partial discharges(PD),which can be analysed to identify specific types of defects.PD clustering is a widely used method to identify PD sources,although its success depends largely on the feature maps used.In this paper,three widely used feature maps,or separation maps,are compared:chromatic,energy wavelet with principal component analysis(EW-PCA),and time-frequency(TF).To compare and evaluate,five scenarios with multi-PD environments with noise were developed.The clustering ability of the maps was evaluated using two performance indicators:intercluster distance and intracluster distance.The results indicate that the EW-PCA map performed the best in all scenarios,correctly identifying the largest number of data points and producing the clearest and most distinct clusters.The TF map created distinct clusters in several scenarios,but not all.The chromatic map created distinct clusters in all scenarios but was not as well defined as the other two separation maps.Given the results,it is important in fieldwork to use a wide range of PD clustering,accompanied by performance metrics that support a less biased decision tailored to the test object.展开更多
Permanent magnet(PM)machines have been widely used in a variety of industrial and military applications due to their definite advantages of high power density and high efficiency.In some applications such as electric ...Permanent magnet(PM)machines have been widely used in a variety of industrial and military applications due to their definite advantages of high power density and high efficiency.In some applications such as electric vehicles(EVs)and aircrafts,high reliability and security of the PM machine are critical.Hence,there is rapidly growing interest in strategies to improve the reliability and security of the PM machine from both academia and industry,where fault diagnosis is a requirement.In this paper,common faults of the PM machine are discussed,state of the art in fault diagnosis of PM machine are overviewed in detail,and different fault diagnosis methods are analyzed and compared.Finally,the development tendency of fault diagnosis techniques for the PM machine is prospected.展开更多
文摘This paper focuses on electrical fault diagnosis and operation and maintenance technology in property service electromechanical engineering.It details core diagnostic methods,application-oriented tools,predictive maintenance frameworks,and enhanced maintenance planning.It also explores wireless sensor networks,big data analytics,and design-phase applications.Case studies in construction and operation phases are presented.Challenges like legacy system retrofitting are noted,and future potential in quantum sensing and edge AI is discussed.
基金This research was funded by science and technology project of State Grid JiangSu Electric Power Co.,Ltd.(Research on Key Technologies of power network security digital identity authentication and management and control based on blockchain,Grant No.is J2021021).
文摘The power infrastructure of the power system is massive in size and dispersed throughout the system.Therefore,how to protect the information security in the operation and maintenance of power equipment is a difficult problem.This paper proposes an improved time-stamped blockchain technology biometric fuzzy feature for electrical equipment maintenance.Compared with previous blockchain transactions,the time-stamped fuzzy biometric signature proposed in this paper overcomes the difficulty that the key is easy to be stolen by hackers and can protect the security of information during operation and maintenance.Finally,the effectiveness of the proposed method is verified by experiments.
文摘VFDs （variable frequency drives） are an integral part of many industrial plants and stations. Reliable operation and maintenance of these drives is vital to ensure sustained plant operation and availability. Understanding of the principles of operation of VFD systems as well as knowledge about their required operating environment is necessary for all operating personnel. Many times the operating personnel do not get involved with different technical issues until a complete failure has occurred. Hence, the awareness of the most dominant failure causes has a significant impact on assisting operators to avoid catastrophic failures and tremendous economic losses due to VFD shutdown. Proper plant design, accurate monitoring and data logging, following manufacturer preventive maintenance schedule, and choosing qualified team of operators can be the key to an efficient operation and a long lifetime for any VFD system. In this paper, we have analyzed the electrical and non-electrical causes of VFD failures based on a case study of a typical medium voltage VFD pumping station. Finally, recommendations are given from field analysis and observations.
基金supported by National Natural Science Foundation of China(61533013,61273144)Scientific Technology Research and Development Plan Project of Tangshan(13130298B)Scientific Technology Research and Development Plan Project of Hebei(z2014070)
文摘In order to study intelligent fault diagnosis methods based on fuzzy neural network (NN) expert system and build up intelligent fault diagnosis for a type of missile weapon system, the concrete implementation of a fuzzy NN fault diagnosis expert system is given in this paper. Based on thorough research of knowledge presentation, the intelligent fault diagnosis system is implemented with artificial intelligence for a large-scale missile weapon equipment. The method is an effective way to perform fuzzy fault diagnosis. Moreover, it provides a new way of the fault diagnosis for large-scale missile weapon equipment.
文摘With the development of large-scale complicated modern power systems, the requirement for the associated protection scheme tends to be more stringent and its combination more complex. However, it is very difficult to figure out the factors of failure of such systems. This paper proposes a Petri net model of a transmission line protection relaying system, including three types of relays as well as an automatic reclosing device, and shows how to diagnose serial failure of the system by analyzing invariant sets of the model. Furthermore, it gives four basic types of failure sequences and its execution is much more intuitive and effective than the traditional method.
基金Joint Funds of the National Natural Science Foundation of China(NSAF)(No.U1330130)General Program of Civil Aviation Flight University of China(No.J2015-39)
文摘To diagnose the aeroengine faults accurately,the supervised Kohonen(S-Kohonen)network is proposed for fault diagnosis.Via adding the output layer behind competitive layer,the network was modified from the unsupervised structure to the supervised structure.Meanwhile,the hybrid particle swarm optimization(H-PSO)was used to optimize the connection weights,after using adaptive inheritance mode(AIM)based on the elite strategy,and adaptive detecting response mechanism(ADRM),HPSO could guide the particles adaptively jumping out of the local solution space,and ensure obtaining the global optimal solution with higher probability.So the optimized S-Kohonen network could overcome the problems of non-identifiability for recognizing the unknown samples,and the non-uniqueness for classification results existing in traditional Kohonen(T-Kohonen)network.The comparison study on the GE90 engine borescope image texture feature recognition is carried out,the research results show that:the optimized S-Kohonen network has a strong ability of practical application in the classification fault diagnosis;the classification accuracy is higher than the common neural network model.
文摘the power network fault detection system can only analyze all kinds of fault signal in stationary sequence： the internal grid and external disturbance presents degeneration, tiny, signal intensity changes randomly fluctuate, that will cause the system to detect the fault isolation ability of confusion and small fault signal is not strong; The article propose a method of power network fault detection for based on GSM, Through the underlying sensing equipment acquisition abnormal information of current, voltage power in the network and GSM networking scheme can filter the interference factors in extraction of fault information from and attribute value. The embedded gateway take STM32 chip as the core to monitoring data processing, to achieve a unified data management and user remote access, realizing method of system software are given, to construct the monitor management information platform. The actual test system show that, identification diagnosis ability of fault signal separation ability and small signal increases 17%, also meet the requirements.
文摘In the contemporary energy landscape,the transition from traditional power grids to smart grids is being increasingly facilitated by the real-time monitoring,protection,and control capabilities provided by wide-area measurement systems.The core of this evolution is the synchrophasor technology,which provides time-synchronized phasor measurements(an essential component for the successful implementation of smart grids).These phasor measurements are acquired through advanced,rapid,time-stamped devices known as phasor measurement units(PMUs),which play a pivotal role in enhancing grid reliability and efficiency.PMUs providehigh accuracy and precision in capturing electric phasors.This advancement has significantly contributed to the reliability of power systems.The data obtained from the PMUs can be applied across a diverse range of contexts and categorized according to their time criticality requirements.Furthermore,the applications can be classified according to their operational foci.A comprehensive review of the pivotal role of PMUs within the context of smart grid systems is presented.It systematically addresses the following key areas:the significance of real-time monitoring and control facilitated by PMUs in smart grids,contribution of PMUs to enhanced situational awareness,utilization of PMU data for state estimation applications,and critical function of PMUs in accurately identifying faults and their locations within the smart grid infrastructure.Additionally,PMU data management is explored.The focus here is on the processes of data acquisition and transmission enabled by PMUs in smart grids and the relevant communication technologies and protocols employed.This study aims to highlight the integral role of PMUs in optimizing the performance and reliability of smart grid networks.
基金support of the Secretaría Nacional de Ciencia,Tecnología e Innovación(SENACYT)under Grant IDDSE19-007the Agencia Nacional de Investigación y Desarrollo(ANID)under Grants Fondecyt 1230135 and Fondef TA24I10002the Sistema Nacional de Investigación(SNI)of Panama under Grant 16-2021.
文摘Electrical insulation faults produce partial discharges(PD),which can be analysed to identify specific types of defects.PD clustering is a widely used method to identify PD sources,although its success depends largely on the feature maps used.In this paper,three widely used feature maps,or separation maps,are compared:chromatic,energy wavelet with principal component analysis(EW-PCA),and time-frequency(TF).To compare and evaluate,five scenarios with multi-PD environments with noise were developed.The clustering ability of the maps was evaluated using two performance indicators:intercluster distance and intracluster distance.The results indicate that the EW-PCA map performed the best in all scenarios,correctly identifying the largest number of data points and producing the clearest and most distinct clusters.The TF map created distinct clusters in several scenarios,but not all.The chromatic map created distinct clusters in all scenarios but was not as well defined as the other two separation maps.Given the results,it is important in fieldwork to use a wide range of PD clustering,accompanied by performance metrics that support a less biased decision tailored to the test object.
基金Supported by the National Key Basic Research Program of China(973 Program)(2013CB035603)the National Natural Science Founda-tion of China(51137001).
文摘Permanent magnet(PM)machines have been widely used in a variety of industrial and military applications due to their definite advantages of high power density and high efficiency.In some applications such as electric vehicles(EVs)and aircrafts,high reliability and security of the PM machine are critical.Hence,there is rapidly growing interest in strategies to improve the reliability and security of the PM machine from both academia and industry,where fault diagnosis is a requirement.In this paper,common faults of the PM machine are discussed,state of the art in fault diagnosis of PM machine are overviewed in detail,and different fault diagnosis methods are analyzed and compared.Finally,the development tendency of fault diagnosis techniques for the PM machine is prospected.
