基于ADAMS的采煤机牵引部轴承故障诊断方法  

Fault Diagnosis Method of Bearing in Shearer Traction Unit Based on ADAMS

作　　者：李晓昆 王然风[1] 王爱玉 付翔[1] LI Xiaokun;WANG Ranfeng;WANG Aiyu;FU Xiang(College of Mining Engineering,Taiyuan University of Technology,Taiyuan,Shanxi 030024,China)

机构地区：[1]太原理工大学矿业工程学院,山西太原030024

出　　处：《矿业研究与开发》2022年第7期184-190,共7页Mining Research and Development

基　　金：山西省应用基础研究计划重点自然基金项目(201901D111007)。

摘　　要：针对采煤机牵引部结构复杂、紧凑,致使采煤机牵引部轴承故障诊断工作困难的问题,提出了基于ADAMS的采煤机牵引部轴承故障诊断方法。首先,以MG210/485-WD型薄煤层采煤机牵引部惰轮轴承为研究对象,利用虚拟样机技术采集正常、内圈故障、滚动体故障、外圈故障等4种状态下轴承的仿真振动信号;然后,将仿真信号导入MATLAB进行基于经验模态分解(EMD)的时频联合处理;最后,针对时频联合处理结果进行特征提取,并利用多种主流分类算法对提取的特征进行训练与测试。信号处理与算法分类结果均表明,基于ADAMS的采煤机牵引部轴承故障诊断方法可以有效地实现轴承故障类别的分类,为采煤机牵引部轴承故障诊断提供了新方法。Due to the complex structure and compactness of the shearer traction unit,the fault diagnosis of the bearing in the shearer traction unit is difficult.In view of this problem,a fault diagnosis method of the bearing in the shearer traction unit based on ADAMS was proposed.Firstly,taking the idler bearing of MG210/485-WD thin coal seam shearer as the research object,the simulation vibration signals of bearings under conditions of normal,inner ring fault,roller fault and outer ring fault were collected by virtual prototype technology.Then,the simulation signals were imported into MATLAB for time-frequency joint processing based on empirical mode decomposition(EMD).Finally,feature extraction was carried out on the time-frequency joint processing results,and a variety of mainstream classification algorithms were used to train and test the extracted features.The results of signal processing and algorithm classification show that the fault diagnosis method of bearing in shearer traction unit based on ADAMS can effectively realize the classification of bearing fault types.The study can provide a new method for fault diagnosis of bearing in shearer traction unit.

关 键 词：采煤机牵引部 轴承 故障诊断 ADAMS 经验模态分解 分类算法 

分 类 号：TD421.6[矿业工程—矿山机电]