Fault diagnosis method of automobile engine based on least squares support vector machine

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 programming 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.