An Adaptive Threshold Based on Support Vector Machine for Fault Diagnosis

被引：0

作者：

Liu, Hongmei ^{[1
]}

Lu, Chen ^{[1
]}

Hou, Wenkui ^{[1
]}

Wang, Shaoping ^{[1
]}

机构：

[1] Beihang Univ, Dept Syst Engn, Beijing 100191, Peoples R China

来源：

PROCEEDINGS OF 2009 8TH INTERNATIONAL CONFERENCE ON RELIABILITY, MAINTAINABILITY AND SAFETY, VOLS I AND II: HIGHLY RELIABLE, EASY TO MAINTAIN AND READY TO SUPPORT | 2009年

关键词：

Adaptive threshold; Support vector machine(SVM); Fault diagnosis; Hydraulic servo system; Actuator;

D O I：

暂无

中图分类号：

V [航空、航天];

学科分类号：

08 ; 0825 ;

摘要：

Considering the drawback of the big en-or when using fixed threshold in fault diagnosis for hydraulic servo system, many factors that may affect the fault threshold are analyzed. By integrating the key factors in threshold model, such as modeling error, random disturbance, input instructions, system current status and etc, an adaptive threshold scheme for fault diagnosis is proposed in this paper, which is based on a pattern recognition algorithm called support vector machine (SVM). It is very effective to adaptively adjust the fault threshold according to a variety of influencing factors. And the robustness is improved by the proposed method, which is verified by experimental results.

引用

页码：907 / 911

页数：5