Fault Diagnosis Method of Automobile Engine Based on Least Squares Support Vector Machine

摘要：

In order to improve diagnostic accuracy and quality of maintenance, it is very important to study fault diagnosis method for automobile engine. Least-squares support vector machine called LSSVM is a modified SVM, which use a set of linear equations instead of a quadratic program ming problem. In the paper, least-squares support vector machine is proposed to fault diagnosis of automobile engine. The LSSVM diagnostic model includes two LSSVMs which are used to recognize the three states of automobile engine including normal state, low-grade accidental fire and serious accidental fire. The experimental data of the relation between waste gas discharge and different accidental fire degree are presented to prove the diagnostic ability of the proposed method. The obtained results indicate that the used LSSVM method can make an effective interpretation in fault diagnosis of automobile engine.

关键词： automobile engine fault diagnosis classification method least squares support vector machine

作者: Qin Bo

作者单位: Institute of Unmanned Aircrafi System BUAA Beijing 100191,China

会议类型: 国际会议

会议名称: 2010 2nd International Conference on Signal Processing System(2010年信号处理系统国际会议 ICSPS 2010)

会议地点: 大连

会议语种:英文

页码: 1724-1727

在线出版日期: 2010-07-05（万方平台首次上网日期，不代表论文的发表时间）