摘要
分析了小波变换的时频局部化特性及基于多分辨分析的信号小波的分解算法 ,研究了信号局部奇异性在小波变换下的特性 ;根据故障信号的局部奇异性在小波变换下模的极大值及其在不同尺度上的传播特性 ,对 30 8型滚动轴承振动加速度故障信号进行分解 ,对故障特征信号进行时域定位 ,并提取了故障特征频率f=46 .88Hz,这与实际的故障特征频率相近 。
The theory of wavelet transform is introduced. The time frequency localization features of the wavelet transform and the signal wavelet transform and the signal wavelet decomposition algorithm based on the multi resolution analysis are analyzed. The signal local singularities during the wavelet transform are studied according to the propagation features of the fault signal modulus maximums during the wavelet transform on the different scales, and by use of the signal wavelet decomposition algorithm. The rolling bearings of 308 type vibration acceleration fault signal is decomposed.The fault characteristic signal on time domain is positioned and the results are given. The fault characteristic frequency is f =46.88 Hz. The results show that the wavelet transform is an efficient method to inspect online and fault diagnosis for the rolling bearings.
出处
《中南工业大学学报》
CSCD
北大核心
2002年第4期434-437,共4页
Journal of Central South University of Technology(Natural Science)
基金
国家海洋技术发展项目(DY10 5 0 3 0 2)
