重庆科技大学学报（自然科学版）2024，Vol.26Issue(5)：107-112,6.DOI:10.19406/j.issn.2097-4531.2024.05.016
基于改进阈值原则与样本熵的轴承阈值降噪方法
The Denoising Method for Bearings Based on the Improved Threshold Principle and Sample Entropy
摘要
Abstract
In order to improve the noise reduction effect of fault bearing signals and reduce the proportion of noise signals in reconstructed signals,a wavelet threshold noise reduction algorithm based on improved threshold principle combined with sample entropy is proposed.The signal is decomposed into multiple layers by wavelet transform,and the thresholds of different decomposition layers are set using the improved threshold principle based on sample en-tropy.Finally,the wavelet coefficients after noise reduction are reconstructed to achieve the final noise reduction of the signal.The results of simulation show that the wavelet threshold noise reduction method based on improved threshold principle can effectively denoise bearing signals,and the noise reduction effect is better than the tradition-al general threshold principle and fixed threshold principle.关键词
改进阈值原则/小波/阈值降噪/样本熵/轴承Key words
improved threshold principle/wavelet/threshold noise reduction/sample entropy/bearing分类
信息技术与安全科学引用本文复制引用
郑威威,刘长松,孙显彬,刘昊..基于改进阈值原则与样本熵的轴承阈值降噪方法[J].重庆科技大学学报（自然科学版）,2024,26(5):107-112,6.基金项目
山东省自然科学基金面上项目"复杂装备智能感知与故障诊断"(ZR2021ME026) （ZR2021ME026）
