Feature Optimization for Bearing Fault Diagnosis

被引：0

作者：

Wang, Mao ^{[1
]}

Hu, Niao-Qing ^{[1
]}

Hu, Lei ^{[1
]}

Gao, Ming ^{[2
]}

机构：

[1] Natl Univ Def Technol, Key Lab Sci & Technol Integrated Logist Support, Changsha, Hunan, Peoples R China

[2] Natl Univ Def Technol, Coll Mechatron & Automat, Res Management Off, Changsha, Hunan, Peoples R China

来源：

PROCEEDINGS OF 2013 INTERNATIONAL CONFERENCE ON QUALITY, RELIABILITY, RISK, MAINTENANCE, AND SAFETY ENGINEERING (QR2MSE), VOLS I-IV | 2013年

基金：

高等学校博士学科点专项科研基金; 中国国家自然科学基金;

关键词：

dimensionless processing methods; rolling bearing fault; feature parameters; evaluation methods;

D O I：

暂无

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

This paper presents methods of feature optimization for bearing fault diagnosis. These methods optimize statistical features in time domain and frequency domain. These optimization methods mainly consist of dimensionless processing and evaluation. Dimensionless processing method is used to avoid the influence of dimension and magnitude to the sensitivity. Fault sensitivity and discrete degree of features are evaluated. And features are selected according to the evaluation results. Analysis results of vibration signals of normal bearings, bearings with outer ring fault, bearings with inner ring fault and bearings with rolling element fault are presented. The results show that these methods are efficient to improve the separability of features.

引用

页码：1738 / 1741

页数：4

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