熵匹配的多重压缩速度同步调频变换及其在轴承故障诊断中的应用
Entropy-Matching-Based Multiple Squeezing Velocity Synchrosqueezing Frequency Modulation Transform and Its Application to Bearing Fault Diagnosis
管迎春 1王文 1何君 1郭光华 1刘继涛 1周鑫 1易灿灿2
作者信息
- 1. 湖北能源集团新能源发展有限公司,湖北武汉 430069
- 2. 武汉科技大学冶金装备及其控制省部共建教育部重点实验室,湖北武汉 430081
- 折叠
摘要
传统时频分析方法处理多分量非平稳信号时表现不佳,特别是在噪声干扰和时频特征快速变化时,时频表示的清晰度和准确性受到严重影响.基于调频变换(CT)衍生的多重压缩速度同步调频变换(MSVSCT)理论,提出一种基于熵匹配的多重压缩速度同步调频变换(E-MSVSCT)的时频分析算法.分析多重压缩速度同步调频变换;利用Renyi熵优化旋转参数,提出了E-MSVSCT方法;最后,利用仿真信号和实验室轴承故障数据对提出方法的有效性进行验证.实验结果表明:E-MSVSCT能够更准确地识别出轴承的时变故障特征频率及其倍频,相比其他方法,其Renyi熵值最低,表现出更高的时频分辨率和噪声鲁棒性.
Abstract
Traditional time-frequency analysis methods perform poorly in dealing with multi-component non-stationary signals,espe-cially facing noise interference and rapid changes in time-frequency characteristics,thus the clarity and accuracy of time-frequency repre-sentations are seriously affected.Based on the theory of multiple squeezing velocity synchrosqueezing chirplet transform(MSVSCT)de-rived from chirplet transform(CT),the time-frequency analysis algorithm based on entropy-matching-based multiple squeezing velocity synchronous chirplet transform(E-MSVSCT)was proposed.Multiple squeezing velocity synchrosqueezing chirplet transform was investiga-ted,and the E-MSVSCT was proposed by optimizing the rotational parameters using Renyi entropy.Finally,the effectiveness of the pro-posed method was verified by using the simulated signals and laboratory bearing fault data.The experimental results show that E-MSVSCT is able to accurately identify the time-varying fault characteristic frequency and their multiplicative frequencies of bearings,it has the low-est Renyi entropy value compared to other methods,and exhibits higher time-frequency resolution and noise robustness.
关键词
同步压缩变换/调频变换/Renyi熵/时频分析/故障诊断Key words
synchrosqueezing transform/chirplet transform/Renyi entropy/time-frequency analysis/fault diagnosis引用本文复制引用
出版年
2024
NETL
NSTL
万方数据