Gear Fault Diagnosis with Support Vector Machine

被引：0

作者：

Tang, Jiali ^{[1
]}

Huang, Chenrong ^{[2
]}

Zuo, Jianmin ^{[1
]}

机构：

[1] Jiangsu Teachers Univ Technol, Coll Comp Engn, Changzhou 213001, Peoples R China

[2] Nanjing Inst Technol, Sch Comp Engn, Nanjing 211167, Jiangsu, Peoples R China

来源：

FUTURE MATERIAL RESEARCH AND INDUSTRY APPLICATION, PTS 1 AND 2 | 2012年 / 455-456卷

关键词：

Neural network; Support Vector Machine; Gear fault diagnosis;

D O I：

10.4028/www.scientific.net/AMR.455-456.1169

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Because of the complexity of gear working condition, there are non-linear relationship between characteristic parameters and fault types. This paper proposes to apply the Support Vector Machine to set up the nonlinear mapping to solve the difficulties of gear fault diagnosis. Taking a certain gearbox fault signal acquisition experimental system for instance, Matlab software and its neural network toolbox are used to model and simulate. The simulation result shows the founded model has preferable learning and generalization capabilities, which performs effectively in the common gear fault diagnosis and it can identify various types of faults stably and accurately.

引用

页码：1169 / +

页数：2

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