Title :
Research of fault prognostic based on LSSVM for electronic equipment
Author :
Ming Yin;Xiaohui Ye; Yanping Tian
Author_Institution :
Dept. of Electronic Engineering, Naval University of Engineering, Wuhan, China
Abstract :
This paper puts forward a method of fault prognostic based on least squares support vector machine for electronic equipment, because fault information of the electronic equipment is insufficient, high incidence of failure. Firstly it introduces the basic principle and the fault prognostic algorithm of the LSSVM process to fault prognostic. Then, fault prognostic research for the electronic equipment can be from a similar analog band-pass filter circuit. Compared to the least square method and support vector machine method, LSSVM method may apply to the different fault condition of the circuit, which obtained the different results. It shows that the proposed method can achieve graded fault prognostic for the analog circuit, and has the better prediction effect.
Keywords :
"Predictive models","Training","Prediction algorithms","Prognostics and health management"
Conference_Titel :
Prognostics and System Health Management Conference (PHM), 2015
DOI :
10.1109/PHM.2015.7380087