摘要
在分析典型声发射(Acoustic emission,AE)信号特征的基础上,根据机械故障或损伤引发的AE信号的故障特征提取原理和特点,首次提出AE信号的小波再分配尺度谱分析法。将小波尺度谱和再分配尺度谱同时用于AE信号的特征提取,再分配尺度谱能提高尺度图的聚集性,减少干扰项,更准确地表征AE信号中的特征信息。通过理论研究和仿真,确定了小波再分配尺度谱基函数及其参数的选择,克服了小波再分配尺度谱的时、频分辨率不能同时达到最好的缺陷。将小波再分配尺度谱用于声发射检测的滚动轴承损伤类型及部件的识别,诊断结果十分直观、清晰、准确。仿真分析和试验研究均表明了小波再分配尺度谱能有效应用于基于声发射技术的状态监测和故障诊断。
By analyzing the typical characteristics of AE signals, and according to the extracting principle of AE signals initiated by mechanical faults or damages, the reassigned wavelet scalogram analysis method of AE signals is put forward for the first time. When wavelet scalogram and reassigned scalogram are applied for the feature extraction of AE signals at the same time, the latter can improve the aggregation of scalogram, reduce interference terms and attribute the feature information of AE signals more accurately. Through theoretical analysis and simulation, the wavelet basis function and parameters are selected, so the problem that the resolutions of time and frequency of wavelet reassigned scalogram connot simultaneously attain the best is solved. When applying wavelet reassigned scalogram is applied for fault diagnosis of rolling beatings based on AE technique, the diagnosis results are quite visualized, clear and accurate. Both simulations and experimental research prove that the wavelet reassigned scalogram effectively used for condition monitoring and fault diagnosis based on AE technique.
出处
《机械工程学报》
EI
CAS
CSCD
北大核心
2009年第2期273-279,共7页
Journal of Mechanical Engineering
基金
湖南省科技计划资助项目(2007FJ3025)
关键词
声发射
小波变换
尺度谱
再分配尺度谱
特征提取
故障诊断
轴承
Acoustic emission Wavelets transform Scalogram Reassigned scalogram Feature extraction Fault diagnosis Bearing
