Fault Prediction of Power-Shift Steering Transmission Based on Support Vector Regression
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 future state of the PSST 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 offered. 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 σare studied using grid search method. And the prediction of spectrometric oil analysis data for PSST is done. A comparative analysis 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 comparative analysis which has important significance for preventing faults.
Fault prediction Power-Shift Steering Transmission (PSST) Support Vector Regression (SVR)
Ying-feng Zhang Biao Ma Jin-song Zhao Hai-ling Zhang
School of Mechanical Engineering Beijing Institute of Technology Beijing,100081,China Academy of Mil Engineering Beijing Institute of Technology Beijing,100081,China Academy of Military Transportation Tianjin, 300161, China
国际会议
2010 IEEE信息与自动化国际会议(ICIA 2010)
哈尔滨
英文
1-5
2010-06-20（万方平台首次上网日期，不代表论文的发表时间）