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Position: Home > Articles > Fault Diagnosis for Rolling Bearings Based on Compressive Sampling Matching Pursuit Journal of Shandong Agricultural University(Natural Science Edition) 2019,50 (3) 524-527

基于压缩采样匹配追踪的滚动轴承故障诊断

作  者:
门超
单  位:
承德石油高等专科学校
关键词:
滚动轴承;故障诊断
摘  要:
滚动轴承在恶劣工况下容易发生损伤,进而影响整个设备安全,基于块坐标松弛算法的形态成分分析方法虽然能够实现信号中各成分的分离,但其计算复杂度较高,不利于滚动轴承的故障特征提取.针对上述问题,本文提出一种基于压缩采样匹配追踪的形态成分分析方法用于诊断轴承故障,以提高诊断的准确性.该方法首先针对信号中的不同成分构造相应的字典,然后在字典上利用压缩采样匹配追踪算法替代形态成分分析方法中的块坐标松弛算法对各成分进行重构,实现噪声和干扰的分离,最终通过包络分析实现滚动轴承的故障诊断.仿真和实验证明了算法的有效性.
译  名:
Fault Diagnosis for Rolling Bearings Based on Compressive Sampling Matching Pursuit
作  者:
MEN Chao;Chengde Petroleum College;
关键词:
Rolling bearing;;fault diagnosis
摘  要:
Rolling bearing is prone to fault because of the severe working conditions. the whole equipment safety is affected.The morphological component analysis method based on the block coordinate relaxation algorithm has high computational complexity and is not conducive to the fault feature extraction of rolling bearings.Therefore, a morphological component analysis method based on compressive sampling matching pursuit is proposed to diagnose bearing faults to improve the accuracy of diagnosis. Firstly, the dictionaries for different components in the signal are constructed. And then the compressive sample matching pursuit algorithm instead of the block coordinate relaxation algorithm is used to reconstruct the components on the dictionary to realize the separation of noise and interference. Finally, envelope analysis is used to realize the fault diagnosis of rolling bearings.

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