机械科学与技术2023，Vol.42Issue(12)：2011-2020,10.DOI:10.13433/j.cnki.1003-8728.20220157
一种二维时频多尺度熵的滚动轴承故障诊断方法
A Two-dimensional Time-frequency Multi-scale Entropy Method for Rolling Bearing Fault Diagnosis
摘要
Abstract
Multi-scale entropy is an effective nonlinear dynamic method to characterize the complexity and irregularity of one-dimensional vibration signal,but it only considers the time-domain complexity of the signal and ignores the frequency-domain information.For comprehensive utilization of the vibration signal frequency domain information and measure of the complexity of the time-frequency distribution characteristics,the two-dimensional multi-scale entropy is introduced into the fault diagnosis of rolling bearings,and a new rolling bearing fault diagnosis method based on two-dimensional time-frequency multi-scale entropy(TFMSE2D)and firefly algorithm optimization support vector machine is proposed.Firstly,a one-dimensional time series is transformed into a time-frequency image by continuous wavelet transform.Secondly,the TFMSE2D of time-frequency image is calculated.Then,the TFMSE2D is input into the firefly optimized support vector machine for classification and prediction.Finally,through the rolling bearing experiment data verify the validity of the proposed method.The results show that the proposed method can accurately identify roller bearing fault type and fault degree.关键词
二维时频多尺度熵/时频分布/滚动轴承/萤火虫优化支持向量机/故障诊断Key words
two-dimensional time-frequency multi-scale entropy/time-frequency distribution/rolling bearing/fireflies optimization support vector machine/fault diagnosis分类
信息技术与安全科学引用本文复制引用
李嘉绮,郑近德,潘海洋,童靳于..一种二维时频多尺度熵的滚动轴承故障诊断方法[J].机械科学与技术,2023,42(12):2011-2020,10.基金项目
国家自然科学基金项目(51975004)与安徽省自然科学基金项目(2008085QE215) （51975004）
