Application Study of Support Vector Regression in State Prediction of PSST
Spectrometric oil analysis technology is an important method in condition monitoring. This method has been applied to study the state of Power-shift Steering Transmission (PSST) in this paper. But, how to predict the PSST future state using existing data is a difficult work. In order to solve this problem, a support vector regression method is applied. The building process of this method is presented. Radial Basis Function (RBF) is selected as the kernel function. This method is applied to study the spectrometric oil analysis data. During the process, the values of parameters γ and σ are studied using grid search method. And 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.
Application study Support Vector Regression (SVR) state prediction PSST (Power-Shift Steering Transmission)
Chen Chengfa Zhang Yingfeng Ma Biao Zhang Hailing
Department of Automobile Engineering,Academy of Military Transportation,Tianjin 300161 China Department of Automobile Engineering,Academy of Military Transportation,Tianjin 300161 China School School of Mechanical Engineering,Beijing Institute of Technology,Beijing 100081 China
国际会议
厦门
英文
1311-1315
2010-05-22（万方平台首次上网日期，不代表论文的发表时间）