中国机械工程

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基于噪声辅助局部波动特征分解的齿轮裂纹故障定量诊断方法

吴家腾1;彭晓燕1;杨宇1;张亢2;程军圣1   

  1. 1. 湖南大学汽车车身先进设计制造国家重点实验室,长沙,410082
    2.长沙理工大学,长沙,410076
  • 出版日期:2016-12-10 发布日期:2016-12-15
  • 基金资助:
    国家自然科学基金资助项目(51575168,51375152,51305046);国家科技支撑计划资助项目(2015BAF32B03);智能型新能源汽车协同创新中心资助项目;湖南省绿色汽车协同创新中心项目 

Quantitative Diagnosis Method of Gear Cracks  Based on Noise-assisted LOD

Wu Jiateng1;Peng Xiaoyan1;Yang Yu1;Zhang Kang2;Cheng Junsheng1   

  1. 1.State key Laboratory of Advanced Design and Manufacture for Vehicle Body, Hunan University, Changsha, 410082
    2.Changsha University of Science and Technology, Changsha, 410076
  • Online:2016-12-10 Published:2016-12-15
  • Supported by:

摘要: 将齿轮故障机理研究与故障诊断方法相结合,提出了一种新的基于噪声辅助局部波动特征分解的齿轮裂纹定量诊断方法。首先,建立了带裂纹齿轮系统动力学模型,获得不同裂纹程度下的动力学响应,从中提取对故障敏感而与工况无关的特征参数构成特征向量矩阵,输入到支持向量回归机中,建立了特征参数与齿轮裂纹程度之间的映射关系。然后,通过这种映射关系,对实际的齿轮裂纹信号采用噪声辅助LOD方法进行特征提取,实现了齿轮裂纹的定量诊断。

关键词: 噪声辅助, 局部波动特征分解;特征提取;映射关系;齿轮裂纹定量诊断

Abstract: A new method of quantitative diagnosis of gear crack faults was proposed based on noise-assisted LOD which combined gear fault mechanism with fault diagnosis methods. Firstly, the feature vector matrixes were constituted by feature parameters which sensitively and independent of working conditions might be extracted from a dynamics model established to obtain the dynamics responses under different levels of cracks and input into the support vector regression(SVR),thus the mapping relationship among feature parameters and levels of gear cracks was created. Based on mapping relationship, the quantitative diagnosis of gear cracks was realized by using noise-assisted LOD extracting feature parameters from actual gear crack signals.

Key words: noise-assisted, local oscillatory-characteristic decomposition(LOD), feature extrac-tion, mapping relationship; , quantitative diagnosis of gear crack

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