摘要
针对滚动轴承早期微弱故障能量小,易受背景噪声干扰的问题,提出了基于谱峭度(SK)和约束独立分量分析(CICA)相结合的方法来提取故障特征。首先,对信号的快速谱峭度图分析得到带通滤波的优化参数,以实现降噪作用;然后,将滤波后的信号作为CICA的输入信号,依据滚动轴承故障特征频率建立参考信号,提取出目标振动信号;最后,利用Teager能量算子解调方法得到信号的能量谱,识别故障特征。
Aiming at low energy of early weak fault of rolling bearings and which is susceptible to interference of background noise,a method is proposed based on spectral kurtosis(SK)and constrained independent component analysis(CICA)to extract fault features.Firstly,the optimal band-pass filter parameters are obtained by analyzing rapid spectral kurtosis of signal to achieve denoising effect.Then,The filtered signals are taken as put signals of CICA.The reference signal is built according to fault feature frequency of rolling bearings,and the target vibration signal is extracted.Finally,the energy spectrum of signal is obtained by using Teager energy operator demodulation method to identify fault feature.
作者
安雪君
郝如江
史云林
AN Xuejun;HAO Rujiang;SHI Yunlin(School of Mechanical Engineering,Shijiazhuang Tiedao University,Shijiazhuang 050043,China)
出处
《轴承》
北大核心
2018年第10期42-46,共5页
Bearing
基金
国家自然科学基金项目(51375319)；河北省杰出青年科学基金项目(E2013210113)
关键词
滚动轴承
故障诊断
谱峭度
约束独立分量分析
TEAGER能量算子
rolling bearing
fault diagnosis
spectral kurtosis
constrained independent component analysis
Teager energy operator
