摘要
针对平方包络信号的负熵对随机脉冲敏感以及平方包络谱的负熵易受离散谐波干扰,从而导致信息图法对随机脉冲和离散谐波分析时鲁棒性差的问题,引入信噪比测度作为轴承故障信息的评估指标,识别包含丰富故障信息的共振频带,并进一步提出基于SNRgram的包络分析方法提取滚动轴承故障特征。仿真和试验结果表明,相对于信息图和其他典型频带识别方法,SNRgram方法处理随机脉冲和离散谐波时具有更强的鲁棒性以及更高的频带识别准确性,能够有效识别轴承故障相关共振频带并提取轴承故障脉冲特征。
The negentropy of squared envelope signal is sensitive to random pulses,and the negentropy of squared envelope spectrum is easily interfered by discrete harmonics,leading to poor robustness of Infogram for analysis of random pulses and discrete harmonics.A signal-to-noise ratio measure is introduced as an evaluation index of bearing fault information and used to identify the resonance frequency band containing abundant fault information.Furthermore,a envelope analysis method based on SNRgram is proposed for extracting the fault features of rolling bearings.The simulation and experimental results show that the SNRgram method is more robust to random pulses and discrete harmonics and has higher frequency band identification accuracy compared with Infogram and other typical frequency band identification methods,and can effectively identify the bearing fault-related resonance frequency band and extract the bearing fault pulse features.
作者
刘妮娜
LIU Nina(Rail Transit Engineering Practice Center,Nanjing Vocational Institute of Railway Technology,Nanjing 210031,China)
出处
《轴承》
北大核心
2023年第1期76-82,共7页
Bearing
关键词
滚动轴承
故障诊断
特征提取
随机脉冲
频带
信噪比
滤波
rolling bearing
fault diagnosis
feature extraction
random pulse
frequency band
signal-to-noise ratio
filtering
