Gear intelligent fault diagnosis based on support vector machines

被引：0

作者：

Lv Peng ^{[1
]}

Liu Yibing ^{[2
]}

Ma Qiang ^{[2
]}

Wei Yufan ^{[2
]}

机构：

[1] North China Elect Power Univ, Sch Math & Phys, Beijing 102206, Peoples R China

[2] North China Elect Power Univ, Dept Automat, Beijing 102206, Peoples R China

来源：

PROCEEDINGS OF THE 26TH CHINESE CONTROL CONFERENCE, VOL 5 | 2007年

关键词：

fault intelligent diagnosis; SVM; gear; feature extraction;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Support Vector Machines (SVM) was used in fault intelligent diagnosis of gear The main research in feature extraction and data preprocess The feature value of time domain includes peak to peak value, absolute average, square root amplitude, mean square amplitude. The feature value of frequency domain is MSF. The SVM method was used for detecting the gear case. The feature of time and the feature of frequent was be used. Through designed a band-pass filter, the feature of gear case's signal was extracted, including feature of time and feature of frequent. The results showed that the reference and fault stations of fan can be distinguished clearly in the SVM diagram. The results showed that it was better than that signals which didn't use filter.

引用

页码：496 / +

页数：2