一种基于MPE与HMM的公交车辆轴承故障诊断方法

Bearing Fault Diagnosis Method Based on MPE and HMMfor Public Traffic Vehicle

针对公交车辆轴承故障易发且其早期故障难以检测的问题,提出了一种基于多尺度排列熵(MPE)与隐马尔可夫模型(HMM)的轴承故障诊断方法。该方法首先对采集的滚动轴承振动信号进行经验模态分解(EMD),分解完成后得到一系列固有模态函数(IMF),选取合适的IMF对信号进行重构,待计算信号多尺度排列熵(MPE)值后再输入已训练收敛的隐马尔模型(HMM)库进行故障类型判别,试验结果验证了该方法的有效性和可行性。

A bearing fault diagnosis method based on multi-scale permutation entropy(MPE)and hidden Markov model(HMM)was proposed for the problem that the bus bearing fault was easy to occur and its early fault was difficult to detect.The method firstly performed empirical mode decomposition(EMD)on the collected rolling bearing vibration signal.After the decomposition,a series of intrinsic mode functions(IMF)were obtained.The appropriate IMF was selected to reconstruct the signal,and the multi-scale entropy of the signal to be calculated was calculated.After the MPE value,the trained concealed hidden-marine model(HMM)library was input to identify the fault type.The experimental results verify the effectiveness and feasibility of the proposed method.