Denoising of Acoustic Emission of Diamond-Coated Mechanical Seals Wear Based on Empirical Wavelet Transform and Kullback-Leibler Divergence

LIN Zhibin; GAO Hongli; WU Yudong; TAN Yongwen

doi:10.3969/j.issn.0258-2724.20210599

Volume 59 Issue 1

Jan. 2024

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Journal of Southwest Jiaotong University > 2024 > 59(1): 177-184.

YAN Zhitao, MA Wenjun, ZHANG Pu, QIU Zhe. Optimization and Tensile Properties of Composite Insulator at High and Low Temperature[J]. Journal of Southwest Jiaotong University, 2021, 56(1): 56-61, 83. doi: 10.3969/j.issn.0258-2724.20181032

Citation:

LIN Zhibin, GAO Hongli, WU Yudong, TAN Yongwen. Denoising of Acoustic Emission of Diamond-Coated Mechanical Seals Wear Based on Empirical Wavelet Transform and Kullback-Leibler Divergence[J]. Journal of Southwest Jiaotong University, 2024, 59(1): 177-184. doi: 10.3969/j.issn.0258-2724.20210599

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Denoising of Acoustic Emission of Diamond-Coated Mechanical Seals Wear Based on Empirical Wavelet Transform and Kullback-Leibler Divergence

doi: 10.3969/j.issn.0258-2724.20210599

School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China

Received Date: 27 Jul 2021
Rev Recd Date: 29 Oct 2021

Available Online: 02 Nov 2022

Publish Date: 03 Nov 2021

Abstract

Abstract

In order to obtain the pure wear acoustic emission of diamond-coated mechanical seal, the denoising method based on empirical wavelet transform (EWT) and Kullback-Leibler divergence (KLD) was proposed. Firstly, filter bank was calculated with empirical wavelet transform on acquired acoustic emission signal. Then the filter bank was applied to both the acquired acoustic emission signal and background noise acoustic emission signal. The Kullback-Leibler divergences were calculated between the corresponding bands of two signals. The cumulative sum algorithm was employed to find a threshold for determining whether the corresponding band is used for signal reconstruction. The results show that the proposed method can effectively suppress the noise of acoustic emission signals under different working conditions and wear states, and effectively improve the signal-to-noise ratio of wear acoustic emission signals, especially weak wear signals. Compared with the traditional denoising methods, the proposed EWT-KLD method has stronger adaptability and stability for denoising of wear acoustic emission signal under different working conditions, which is of great significance for the monitoring early seal wear and the cumulative wear process of seal.
- mechanical seal,
- acoustic emission denoising,
- empirical wavelet transform,
- diamond coating

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References(28)

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