基于小波包变换及RBF神经网络的继电器寿命预测

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Abstract The performance parameters sequential values of relay is non-stationary time series,In order to predict the working life of relay accurately, this paper improves the wavelet packet transform theory and using the improved wavelet packet transform theory to decompose relay overtravel time runoff of non-stationary characteristics, so that the smooth item and random item separation, for the smooth item ,using traditional AR model to predict; for random item, the RBF(radial basis function) neural network prediction model which is based on phase space reconstruction is established to predict. Finally, the results of two predict models were reconstructed through the wavelet packet reconstruction method to predict the original non-stationary runoff series. Through an example verified that this method has higher accuracy and it is an feasible method.

Key words： Wavelet packet transform runoff series wavelet packet reconstruction AR model

Received: 20 September 2014 Published: 08 September 2015

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	Articles by authors
	Li Zhigang
	Liu Boying
	Li Lingling
	Sun Dongwang

Cite this article:

Li Zhigang,Liu Boying,Li Lingling等. Life Prediction of Relay Based on Wavelet Packet Transform and RBF Neural Network[J]. Transactions of China Electrotechnical Society, 2015, 30(14): 233-240.

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https://dgjsxb.ces-transaction.com/EN/ OR https://dgjsxb.ces-transaction.com/EN/Y2015/V30/I14/233

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