摘要
针对现有信号降噪或重构方法无法完全去除噪声,且时频表示存在能量模糊问题,提出了一种利用元素分析进行滚动轴承故障诊断的方法。所提方法首先构造了元素模型来表征信号,然后对元素模型进行Morse小波变换,并从小波变换中计算得出信号冲击点,从而得到信号的故障特征频率。该方法还可以利用基于小波变换中时间或尺度平面内的少量孤点来重构信号。最后,采用一组仿真信号数据和两组实验数据来评估所提方法性能,并与其他信号重构方法和时频分析方法对比,结果表明,所提方法对滚动轴承故障信号重建和识别的效果更好。
Given the existing signal denoising or reconstruction methods can not completely remove the noise,and the time-frequency representation has the problem of energy ambiguity,a method for rolling bearing fault diagnosis based on element analysis was proposed.Firstly,the proposed method constructs an elemental model to characterize the signal,then the Morse wavelet transform is applied to the elemental model and the impact point of the signal is calculated from the wavelet transform to obtain the characteristic defect frequency of the signal.Based on a small number of solitary points in the time or scale plane of the wavelet transform,the method is used to reconstruct the signal.In this paper,a set of simulated signal data and two sets of experimental data are used to estimate the performance of the method and compare it with other signal reconstruction methods and time-frequency analysis methods.The results demonstrate that the proposed method has a good performance in the identification and reconstruction of rolling bearing fault signals.
作者
戴含芳
王衍学
李志星
Dai Hanfang;Wang Yanxue;Li Zhixing(School of Mechanical-Electronic and Vehicle Engineering,Beijing University of Civil Engineering and Architecture,Beijing 100044,China;Beijing Key Laboratory of Performance Guarantee on Urban Rail Transit Vehicles,Beijing University of Civil Engineering and Architecture,Beijing 100044,China)
出处
《电子测量与仪器学报》
CSCD
北大核心
2022年第1期157-165,共9页
Journal of Electronic Measurement and Instrumentation
基金
国家自然科学基金项目(51875032)
北京市百千万人才项目
西城区拔尖创新团队
北京建筑大学2021年度研究生创新项目资助
关键词
旋转机械
元素分析
Morse小波
故障特征提取
信号重建
rotating machinery
elemental analysis
Morse wavelet
fault feature extraction
signal reconstruction
作者简介
戴含芳,2019年于北京建筑大学获得学士学位,现为北京建筑大学硕士研究生,主要研究方向为信号处理与特征提取。E-mail:daihhh@163.com;王衍学,2009年于西安交通大学获得博士学位,2010~2011年加拿大渥太华大学博士后,现为北京建筑大学教授、博导,主要研究方向为装备故障诊断与智能维护、剩余寿命与健康管理及信号处理与特征提取等。E-mail:wyx1999140@126.com;李志星,2018年于北京科技大学博士学位,2018~2020年北京航空航天大学博士后,现为北京建筑大学讲师、硕导,主要研究方向为机械设备早期微弱故障诊断、振动信号处理等。E-mail:lizhixing@bucea.edu.cn
