Motor current signature analysis provides good results in laboratory environment. In real life situation, electrical machines usually share voltage and current from common terminals and would easily influence each oth...Motor current signature analysis provides good results in laboratory environment. In real life situation, electrical machines usually share voltage and current from common terminals and would easily influence each other. This will result in considerable amount of interferences among motors and doubt in identity of fault signals. Therefore, estimating the mutual influence of motors will help identifying the original signal from the environmental noise. This research aims at modelling the propagation of signals that are caused by faults of induction motors in power networks. Estimating the propagation pattern of fault signal leads to a method to discriminate and identify the original source of major events in industrial networks. Simulation results show that source of fault could be identified using this approach with a higher certainty than anticipated output coming of any individual diagnosis.展开更多
To effectively extract the interturn short circuit fault features of induction motor from stator current signal, a novel feature extraction method based on the bare-bones particle swarm optimization （BBPSO） algorith...To effectively extract the interturn short circuit fault features of induction motor from stator current signal, a novel feature extraction method based on the bare-bones particle swarm optimization （BBPSO） algorithm and wavelet packet was proposed. First, according to the maximum inner product between the current signal and the cosine basis functions, this method could precisely estimate the waveform parameters of the fundamental component using the powerful global search capability of the BBPSO, which can eliminate the fundamental component and not affect other harmonic components. Then, the harmonic components of residual current signal were decomposed to a series of frequency bands by wavelet packet to extract the interturn circuit fault features of the induction motor. Finally, the results of simulation and laboratory tests demonstrated the effectiveness of the proposed method.展开更多
在分析有源配电网故障电流特征的基础上,分析了分布式电源(distributed electric resources,DER)对配电网继电保护可能产生的影响。根据是否影响配电网继电保护的正确动作以及是否需要采取克服其影响的技术措施,将DER对配电网继电保护...在分析有源配电网故障电流特征的基础上,分析了分布式电源(distributed electric resources,DER)对配电网继电保护可能产生的影响。根据是否影响配电网继电保护的正确动作以及是否需要采取克服其影响的技术措施,将DER对配电网继电保护的影响程度分为没有实质性影响、有一定影响与严重影响3个级别。基于线路上DER输出的最大短路电流,提出了DER对配电网继电保护影响的评估方法。最后,结合示例证明了该方法评估DER对配电网继电保护的影响的有效性和实用性。展开更多
文摘Motor current signature analysis provides good results in laboratory environment. In real life situation, electrical machines usually share voltage and current from common terminals and would easily influence each other. This will result in considerable amount of interferences among motors and doubt in identity of fault signals. Therefore, estimating the mutual influence of motors will help identifying the original signal from the environmental noise. This research aims at modelling the propagation of signals that are caused by faults of induction motors in power networks. Estimating the propagation pattern of fault signal leads to a method to discriminate and identify the original source of major events in industrial networks. Simulation results show that source of fault could be identified using this approach with a higher certainty than anticipated output coming of any individual diagnosis.
文摘To effectively extract the interturn short circuit fault features of induction motor from stator current signal, a novel feature extraction method based on the bare-bones particle swarm optimization （BBPSO） algorithm and wavelet packet was proposed. First, according to the maximum inner product between the current signal and the cosine basis functions, this method could precisely estimate the waveform parameters of the fundamental component using the powerful global search capability of the BBPSO, which can eliminate the fundamental component and not affect other harmonic components. Then, the harmonic components of residual current signal were decomposed to a series of frequency bands by wavelet packet to extract the interturn circuit fault features of the induction motor. Finally, the results of simulation and laboratory tests demonstrated the effectiveness of the proposed method.
文摘在分析有源配电网故障电流特征的基础上,分析了分布式电源(distributed electric resources,DER)对配电网继电保护可能产生的影响。根据是否影响配电网继电保护的正确动作以及是否需要采取克服其影响的技术措施,将DER对配电网继电保护的影响程度分为没有实质性影响、有一定影响与严重影响3个级别。基于线路上DER输出的最大短路电流,提出了DER对配电网继电保护影响的评估方法。最后,结合示例证明了该方法评估DER对配电网继电保护的影响的有效性和实用性。
