安全、健康和环境2024，Vol.24Issue(7)：21-28,8.DOI:10.3969/j.issn.1672-7932.2024.07.004
基于频域子空间字典学习的干气密封声发射信号降噪方法
A Noise Reduction Method for Acoustic Emission Signals of Dry Gas Seals Based on Frequency Subspace Dictionary Learning
摘要
Abstract
Aiming at the problems of low signal-to-noise ratio and susceptibility to background noise in-terference in dry gas seal acoustic emission signals,a denoising method based on frequency domain sub-space dictionary learning was proposed.Firstly,ob-tain the mutual relationship between each frequency band based on adjacent relevant information of the time-frequency distribution of the acoustic emission signal.Based on this,the boundary of the frequency domain division was determined,and the correspond-ing empirical wavelet family was constructed.The sparse reconstruction of the acoustic emission signal was carried out in each subspace using the time shift invariant dictionary learning algorithm.On this ba-sis,the kurtosis index of the reconstructed signal was used to weight each component.The experimental re-sults showed that the proposed algorithm improves the signal kurtosis index from 48.43 to 185.93,achie-ving noise reduction of acoustic emission signals and enhancement of collision and wear characteristics dur-ing dry gas sealing start-up process.关键词
干气密封/声发射/经验小波变换/稀疏字典学习/信号降噪Key words
dry gas seal/acoustic emission/empiri-cal wavelet transform/sparse dictionary learning/sig-nal noise reduction分类
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黄鑫,马骏,陈文武,屈定荣,刘景明..基于频域子空间字典学习的干气密封声发射信号降噪方法[J].安全、健康和环境,2024,24(7):21-28,8.基金项目
中国石油化工股份公司科技部项目(323031),干气密封故障特征研究及监测技术. （323031）
