TY - GEN
T1 - Fault prediction of power-shift steering transmission based on support vector regression
AU - Zhang, Ying Feng
AU - Ma, Biao
AU - Zhao, Jin Song
AU - Zhang, Hai Ling
PY - 2010
Y1 - 2010
N2 - 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 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.
AB - 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 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.
KW - Fault prediction
KW - Power-Shift Steering Transmission (PSST)
KW - Support Vector Regression (SVR)
UR - http://www.scopus.com/inward/record.url?scp=77955762756&partnerID=8YFLogxK
U2 - 10.1109/ICINFA.2010.5512075
DO - 10.1109/ICINFA.2010.5512075
M3 - Conference contribution
AN - SCOPUS:77955762756
SN - 9781424457021
T3 - 2010 IEEE International Conference on Information and Automation, ICIA 2010
SP - 273
EP - 277
BT - 2010 IEEE International Conference on Information and Automation, ICIA 2010
T2 - 2010 IEEE International Conference on Information and Automation, ICIA 2010
Y2 - 20 June 2010 through 23 June 2010
ER -