基于小波包分析和概率神经网络的电磁法三电平变换器故障诊断方法

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Abstract According to the fault characteristics and complex working environment of electromagnetic transmitters,a novel fault diagnosis method is proposed to solve the open-circuit fault of three-level inverters based electromagnetic transmitters.the wavelet packet analysis (WPA) is adopted to extract the feature vector of the open-circuit fault output voltage which is used as the original signal.The sample frequency is set to be variable to improve the frequency resolution of WPA.The kernel principal component analysis (KPCA) is employed to reduce the dimension of feature vector,which can simplify the structure of classifier and decrease the time of diagnosis.The probabilistic neural network (PNN) has strong fault tolerance and can be used to establish the fault classifier.A 5 kW laboratory prototype has been built.Experimental results show that the method can effectively diagnose the open-circuit fault and realize real-time fault diagnosis,which has good diagnosis accuracy and strong robustness.And the proposed method has some contribution in practical applications.

Key words： Three-level inverter electromagnetic transmitter wavelet packet analysis kernel principal component analysis probabilistic neural networks fault diagnosis

Received: 13 May 2015 Published: 18 September 2016

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TP277

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	Yu Shengbao
	He Jianlong
	Wang Ruijia
	Li Gang
	Su Fa

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Yu Shengbao,He Jianlong,Wang Ruijia等. Fault Diagnosis of Electromagnetic Three-Level Inverter Based on Wavelet Packet Analysis and Probabilistic Neural Networks[J]. Transactions of China Electrotechnical Society, 2016, 31(17): 102-112.

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https://dgjsxb.ces-transaction.com/EN/ OR https://dgjsxb.ces-transaction.com/EN/Y2016/V31/I17/102

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