Rolling bearing fault feature extraction method based on modulation enhanced slice MSB
FENG Kun1, YAN Kang1, HU Minghui2, HE Ya1,2, JIANG Zhinong1,2
1. MOE Key Lab of Engine Health Monitoring-Control and Networking, Beijing 100029, China;
2. Beijing Municipal Key Lab of Health Monitoring and Self-healing of High-level Mechanical Equipment, Beijing 100029, China
摘要针对快速谱峭度图和传统切片MSB(modulation signal bispectrum)算法在强干扰条件下提取轴承故障特征不佳的问题，提出一种基于调制增强切片MSB的滚动轴承故障特征提取方法。首先利用MSB算法计算得到原始振动信号的调制信号双谱，对主维度进行切片叠加得到载波谱；然后基于MSB凸显滚动轴承故障信号调制特征的性质，通过粒子群寻优算法对切片范围进行择优；最后，对故障特征所在切片的双谱相干函数与调制信号双谱进行组合处理，进行增强性重构得到调制谱，去除了大部分噪声分量，直接提取出故障特征。通过仿真、实验验证了调制增强切片MSB算法能够实现长传递路径、强噪声干扰条件下的滚动轴承故障特征提取，所得结果比快速谱峭度图更加直观、清晰。
Abstract：Aiming at poor performance of the fast spectral kurtosis diagram and the traditional slice MSB (modulation signal bispectrum) algorithm in extracting bearing fault features under strong interference conditions, a rolling bearing fault feature extraction method based on the modulation enhanced slice MSB algorithm was proposed. Firstly, MSB algorithm was used to do calculation and obtain MSB of the original vibration signal, and the carrier spectrum was obtained by slicing and superposing main dimension slices. Secondly, based on the property of MSB highlighting modulation characteristics of rolling bearing fault signal, the slicing range was optimized using the PSO algorithm. Finally, the bispectral coherence function of the slice where fault feature was located and the modulated signal bispectrum were combined to get the modulation spectrum through the enhanced reconstruction. Thus, most of noise components were removed, and fault features were extracted directly. The results of simulation and tests showed that the proposed modulation enhanced slice MSB algorithm can realize rolling bearing fault feature extraction under conditions of long transmission path and strong noise interference; the results obtained with this algorithm are more intuitive and clearer than those obtained with the fast spectral kurtosis diagram.
冯坤1，颜康2，胡明辉2，贺雅1,2,江志农1,2. 基于调制增强切片MSB的滚动轴承故障特征提取方法[J]. 振动与冲击, 2021, 40(13): 182-192.
FENG Kun1, YAN Kang1, HU Minghui2, HE Ya1,2, JIANG Zhinong1,2. Rolling bearing fault feature extraction method based on modulation enhanced slice MSB. JOURNAL OF VIBRATION AND SHOCK, 2021, 40(13): 182-192.
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