基于形态小波与排列熵的变速器齿轮故障识别方法  

Fault Recognition Method of Transmission Gear based on Morphological Wavelet and Permutation Entropy

作　　者：丁伟[1] 张志刚[2] 姚练红 黄捷 Ding Wei;Zhang Zhigang;Yao Lianhong;Huang Jie(School of Intelligent Manufacturing and Automotive,Chongqing College of Electronic Engineering,Chongqing 401331,China;Key Laboratory of Advanced Manufacture Technology for Automobile Parts of Ministry of Education,Chongqing University of Technology,Chongqing 400054,China;Technology Center,Chongqing Qing Shan Industrial Co.,Ltd.,Chongqing 402761,China)

机构地区：[1]重庆电子工程职业学院智能制造与汽车学院,重庆401331 [2]重庆理工大学汽车零部件先进制造技术教育部重点实验室,重庆400054 [3]重庆青山工业有限责任公司技术中心,重庆402761

出　　处：《机械传动》2019年第10期165-168,共4页Journal of Mechanical Transmission

基　　金：重庆市教委科学技术研究项目(KJ1602902)

摘　　要：在深入研究形态小波与排列熵的基础上,提出一种新的变速器齿轮故障识别方法。引入形态小波的概念,提出采用形态Haar小波对实测变速器齿轮振动信号进行降噪预处理;将排列熵作为变速器齿轮故障的特征值,提取了包括齿轮正常、齿面轻度磨损、齿面中度磨损和断齿等4种工况的振动信号;依据不同的故障对应不同的排列熵分布,对各种故障状态进行分类,同时对比了未降噪信号的排列熵分布。变速器齿轮故障识别的实例验证了形态小波与排列熵结合能有效提高齿轮故障分类能力。Based on the in-depth study on morphological wavelet with permutation entropy,a new method for gear of transmission fault recognition is proposed.Firstly,the definition of morphological wavelet is intro duced,and the morphological Haar wavelet is used to pre-process the measured gear of transmission vibration signal.Then,the permutation entropy is used as the eigenvalue of gear fault to extract the vibration signal,which included four working conditions:normal,slight-worn,medium-worn and broken teeth.Finally,according to dif ferent faults corresponding to different permutation entropy distributions,the various fault states are classified,and the permutation entropy distributions of non-denoised signals are compared.The example of gear fault rec ognition proved that the combination of morphological wavelet and permutation entropy could effectively im prove the ability of gear of transmission fault classification.

关 键 词：变速器 齿轮 形态小波 排列熵 故障识别 

分 类 号：U46[机械工程—车辆工程]