基于ITD 与样本熵的汽车变速箱故障特征提取方法研究  

Research on Extraction Method of Automobile Gearbox Fault Features Based on ITD and Sample Entropy

作　　者：刘国弟 赵伟杰 王树恒 Liu Guodi;Zhao Weijie;Wang Shuheng(Chery Automobile Co.,Ltd,Anhui Wuhu 241000)

机构地区：[1]奇瑞汽车股份有限公司,安徽芜湖241000

出　　处：《汽车实用技术》2020年第23期99-101,共3页Automobile Applied Technology

摘　　要：针对汽车变速箱齿轮振动信号的非线性和非平稳性,采用ITD-样本熵方法来进行故障的特征提取。首先用ITD分解方法把原始信号分解成一系列PR分量。因为PR1和PR2分量和原始信号的相关系数远高于其他分量,因此最能反映信息的真实状态。然后计算齿轮不同故障状态PR1和PR2分量的ITD-样本熵值,其大小关系呈现为正常>齿根裂纹>断齿>缺齿,有迹可循。说明利用ITD-样本熵方法进行变速箱齿轮故障诊断是可行且有效的。For the non-linear and the non-stationary characteristics of gear faults signal,ITD-sample entropy method is used to extract the feature of the fault.First,the ITD decomposition method is used to decompose the original signal into a series of PR components.Because the correlation coefficients of the PR1 and PR2 components and the original signal are much higher than other components,they can best reflect the true state of the information.Then calculate the ITD-sample entropy values of the PR1 and PR2 components,and the size relationship is normal>root crack>broken tooth>missing tooth.It shows that it is feasible and effective to use the ITD-sample entropy method for gearbox gear fault diagnosis.

关 键 词：非线性 ITD 样本熵 故障特征 齿轮 

分 类 号：TP277[自动化与计算机技术—检测技术与自动化装置]