中国电机工程学报Issue(20)：111-118,8.
基于信号共振稀疏分解与能量算子解调的轴承故障诊断方法
Fault Diagnosis of Rolling Bearings Based on Resonance-based Sparse Signal Decomposition and Energy Operator Demodulating
摘要
Abstract
When local defects occurred in a rolling bearing, the vibration signal of the rolling bearing always has periodic impulse components. Furthermore, rolling bearings often run under complex working conditions and the vibration signals usually accompany with other components such as rotating harmonic components and noises. Therefore, it is difficult to detect a rolling bearings’ fault by making demodulating analysis on the vibration signal of the rolling bearing. Aiming at this problem, a fault diagnosis method of rolling bearings based on the resonance-based sparse signal decomposition and energy operator demodulating was proposed. This method separated the impulse from the vibration signals of a rolling bearing by using resonance-based sparse signal decomposition. Using energy operator demodulating to calculate the instantaneous amplitude, then the cycle of the impulse component can be acquired from the spectrum of the instantaneous amplitude and the rolling bearing fault can be diagnosed. Simulation and application examples have proved the effectiveness of the method.关键词
共振稀疏分解/品质因子/能量算子解调/轴承/故障诊断Key words
resonance-based sparse signal decomposition/Q-factor/energy operator demodulating/rolling bearing/fault diagnosis分类
机械制造引用本文复制引用
..基于信号共振稀疏分解与能量算子解调的轴承故障诊断方法[J].中国电机工程学报,2013,(20):111-118,8.基金项目
国家自然科学基金项目(5127516)。 （5127516）
