基于经验模式分解和Teager能量谱的齿轮箱故障诊断

Gearbox fault diagnosis based on empirical mode decomposition and Teager energy spectrum

在线监测汽车齿轮变速箱运转工作状态,及时发现齿轮箱的早期故障,对汽车运行的安全性有重要意义。利用经验模式分解和Teager能量谱对振动加速度传感器获取的齿轮箱振动信号进行特性分析。先利用经验模式分解获得故障信号的本征模式函数,然后计算本征模式函数Teager能量谱,提取本征模式函数系数-能量谱特征值来分析时频故障特性。仿真研究结果表明用Teager能量特征表达在故障定位和故障信息提取方面是可行的和有效的,提高了故障检测的可靠性。

It is significant for automobile security to study how to monitor operating state of automobile gearbox and detect incipient faults as soon as possible.Characteristics analysis for gearbox vibration signals captured from vibrating acceleration sensors based on empirical mode decomposition (EMD) and Teager energy spectrum was proposed.The fault detection signal was firstly decomposed into intrinsic mode functions (IMF) with the EMD method.Then,Teager energy spectrum of each intrinsic mode function was obtained using Teager energy operator.Finally,the time-frequency fault characteristics of a gearbox were analyzed by means of the coefficient-energy spectrum values of intrinsic mode functions.Experiment results showed the feasibility and efficiency of the EMD and Teager energy characteristic method in fault location and fault information extraction,and that the algorithm is very reliable to be implemented for fault detection.