齿轮箱故障诊断的启动电流阶次分析方法研究  

Study on Gear Fault Diagnosis Method Using the Order Analysis of Startup Current

作　　者：张思敏 任芳[1,2] 杨兆建 李峰[1,2] ZHANG Si-min;REN Fang;YANG Zhao-jian;LI Feng(College of Mechanical Engineering,Taiyuan University of Technology,Shanxi Taiyuan 030024,China;Key Laboratory of Fully Mechanized Coal Mining Equipment of Shanxi Province,Shanxi Taiyuan 030024,China)

机构地区：[1]太原理工大学机械工程学院,山西太原030024 [2]煤矿综采装备山西省重点实验室,山西太原030024

出　　处：《机械设计与制造》2020年第12期39-43,共5页Machinery Design & Manufacture

基　　金：国家自然科学基金项目资助(51475318)。

摘　　要：针对电机驱动的齿轮传动系统在故障诊断中的特点及存在的问题,提出了一种基于电机启动电流的无转速计阶次分析方法。该方法通过Hilbert-Huang时频分析对电机启动电流信号经EMD分解后的敏感IMF分量进行瞬时频率估计,实现了对电机转速信号的拟合;通过对启动电流的等角度重采样信号进行快速傅里叶变换,最终实现阶次分析。与传统分析方法相比,该方法避免了传统电机电流特征分析法存在的故障特征分量容易被湮没的问题;克服了传统频谱分析方法无法分析非稳态信号的不足;同时由于仅需测量电机电流信号即可实现故障诊断,有效降低了因齿轮箱实际复杂工作环境对测量操作的难度。实验结果表明:此方法能够有效识别启动过程中齿轮箱的故障特征分量。In view of the characteristics and problems of the gear system driven by motor in fault diagnosis,an order analysis method with no-tachometer based on motor starting current is presented.Firstly,this method completed the fitting of the motor speed signal by the estimation of the instantaneous frequency which using sensitive IMF component from EMD decomposition of the motor starting current signal through the Hilbert-Huang time-frequency analysis.Finally,it completed the order analysis of the starting current signal by doing FFT to the even-angle resampling signal.Compared with the traditional analysis method,this method avoids the problem that the fault characteristic components are easily annihilated in the old way.And it overcomes the shortcomings that the traditional frequency analysis method cannot analyze the unsteady state signal.At the same time,the method effectively reduced the difficulties in measuring and the environmental restrictions of the gear box,as a result of it needs only the motor current signal.The experimental results show that this method can effectively identify the fault feature components of gearbox during start-up process.

关 键 词：故障诊断 启动电流 等角度重采样 阶次分析 

分 类 号：TH16[机械工程—机械制造及自动化] TH113.1