Title :
Study on Condition Monitoring of Power-Shift Steering Transmission Based on Support Vector Machine
Author :
Zhang, Ying-Feng ; Ma, Biao ; Zhu, Yuan ; Zhang, Jin-Le
Author_Institution :
Sch. of Mech. Eng., Beijing Inst. of Technol., Beijing, China
Abstract :
This paper is aimed at the condition monitoring problem of the Power-shift Steering Transmission (PSST), a method of multiple out least squares support vector regression is developed which is applied to prediction of spectrometric oil analysis data. Radial Basis Function (RBF) is used is this algorithm. There are two parameters ¿ and ¿2. The selection of ¿ and ¿2 is studied using cross validation method with spectrometric oil analysis data. The prediction of spectrometric oil analysis data for PSST is done. A comparative analysis is made between predictive and actual values. The method has been proved that it has better accuracy in prediction, and any possible problem in PSST can be found through a comparative analysis which has important significance for preventing faults.
Keywords :
condition monitoring; mechanical engineering computing; power transmission (mechanical); radial basis function networks; steering systems; support vector machines; condition monitoring; multiple out least squares support vector regression; power-shift steering transmission; radial basis function; spectrometric oil analysis; support vector machine; Condition monitoring; Data analysis; Data mining; Least squares methods; Mechanical engineering; Paper technology; Petroleum; Spectroscopy; Support vector machine classification; Support vector machines;
Conference_Titel :
Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-4507-3
Electronic_ISBN :
978-1-4244-4507-3
DOI :
10.1109/CISE.2009.5364068
