基于波形匹配端点延拓法优化的经验模态分解算法在铁路继电器参数降噪上的应用

doi:10.19595/j.cnki.1000-6753.tces.201491

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Abstract Aiming at the noise problem of railway relay parameters,this paper establishes a hybrid noise reduction model based on empirical mode decomposition algorithm optimized by the improved waveform matching continuation method to extract the effective information.This model uses autocorrelation function to separate noisy signals and wavelet threshold to remove noise. Firstly, according to the characteristics of relay parameters, the waveform matching method is improved.The matching error degree formula is redefined, and the matching accuracy error coefficient is introduced. The end effect produced by EMD decomposition process is optimized by the improved waveform matching continuation method, and the effective IMF component and residual term are obtained. Then, the autocorrelation function is solved, and the noise signal feature is separated according to the autocorrelation function image. Finally, the noisy component is denoised by wavelet threshold. After denoising, it is combined with the residual component and remainder to obtainthe reconstructed parameter sequence. Moreover, the SSIM index, SNR and MSE index are used to evaluate the reliability of the model. Compared with EMD reconstruction and the wavelet threshold de-noising method, the noise reduction effect of the model is proved.

Key words： Endpoint effect waveform matching endpoint continuation method autocorrelation function structural similarity index measurement (SSIM) index

Received: 14 November 2020

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	Li Wenhua
	Jiang Hui
	Zhao Zhengyuan
	Pan Ruzheng
	Hu Kangsheng

Cite this article:

Li Wenhua,Jiang Hui,Zhao Zhengyuan等. Application of Empirical Mode Decomposition Algorithm Based on Waveform Matching Endpoint Continuation Method in Noise Reduction of Railway Relay Parameters[J]. Transactions of China Electrotechnical Society, 2022, 37(10): 2656-2664.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.201491 OR https://dgjsxb.ces-transaction.com/EN/Y2022/V37/I10/2656

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