摘要
时频分析是提取轴承故障诊断的重要方法,在强背景噪声下难以提取瞬态故障特征。针对这一问题,提出一种基于Teager-Kaiser能量算子(TKEO)和同步提取变换(SET)的轴承故障诊断方法,提高SET的时频分析能量的集中度。该方法首先对采集的轴承振动信号进行提取TKEO处理,凸显轴承故障振动信号的冲击分量;然后,对处理后信号进行SET时频分析,通过同步提取算子(SEO)提取时频脊线的时频系数,实现对瞬态故障特征提取;最后通过仿真信号和实测信号进行分析,验证该方法的可行性。实验结果表明:该方法可以有效提取轴承的故障特征,且与先前的时频分析方法相比分析结果具有一定的优越性。
Time-frequency analysis is an important method for extracting bearing fault diagnosis,and it is difficult to extract transient fault features under strong background noise.To address this problem,a bearing fault diagnosis method based on Teager-Kaiser energy operator(TKEO)and synchroextracting transform(SET)is proposed to improve the concentration of the energy of time-frequency analysis of SET.The method firstly extracts the TKEO processing of the collected bearing vibration signal to highlight the impact component of the bearing fault vibration signal;then,the processed signal is subjected to SET analysis,and the time-frequency coefficients of the time-frequency ridges are extracted by the synchroextracting operator(SEO)to realize the extraction of transient fault features;finally,the feasibility of the method is verified by analyzing the simulated signal and the measured signal.The experimental results show that the method can effectively extract the fault characteristics of the bearing,and the analysis results have certain superiority compared with the previous time-frequency analysis methods.
作者
陈志刚
姜云龙
王莹莹
何群
张怀彬
Chen Zhigang;Jiang Yunlong;Wang Yingying;He Qun;Zhang Huaibin(School of Mechanical Electronic and Vehicle Engineering,Beijing University of Civil Engineering and Architecture,Beijing 100044,China;Beijing Construction Safety Monitoring Engineering Technology Research Center,Beijing 100044,China)
出处
《电子测量技术》
北大核心
2022年第10期155-160,共6页
Electronic Measurement Technology
基金
北京建筑大学市属高校基本科研业务费专项资金(X20061)
北京市建筑安全监测工程技术研究中心研究基金资助课题(BJC2020K011)资助
