滚动轴承复合故障诊断的自适应方法研究

摘要

In the process of bearing inspection of freight cars,compound faults are prevalent.Aiming at improving the difficulty of separating the compound fault features from a single-channel vibration signal,an adaptive fault diagnosis method based on notch filter was proposed.The original compound fault vibration signals were decomposed by using the empirical mode decomposition (EMD).Then the vibration signals were reconstructed in accordance with the principle of maximum correlation coefficients between the intrinsic mode functions (IMFS)and the original signal and the spectrum analysis was utilized to identify the primary fault.Then,the primary fault signal was filtered out from the original signal with the adaptive notch filter system,and subordinate faults were diagnosed through the filtered signal.The results of simulation and experimental signals indicate that the adaptive fault diagnosis method based on notch filer can extract the features of primary and subordinate faults from compound fault signals and is valuable for engineering application.%铁路货车滚动轴承检测中多种故障共存的情况普遍存在。针对单通道情况下复合故障难分离和诊断的问题，提出了基于陷波器的自适应复合故障诊断方法。该方法首先对滚动轴承的复合故障振动信号进行经验模态分解（Empirical Mode Decomposition，EMD），根据各个本征模态函数与原始信号的相关系数最大化原则对信号进行重构，进一步通过频谱分析识别出滚动轴承主故障。在此基础上，利用自适应陷波器系统对原始振动信号的主故障信号进行陷波处理。然后再对筛去主故障信息的信号进行次故障诊断。通过仿真和实验分析，结果表明基于陷波器的自适应复合故障诊断方法能在一定程度上满足复合故障信号分离和故障诊断的要求，具有一定的实用性。