A method of multiple outputs least squares support vector regression (LS-SVR) was developed and described in detail, with the radial basis function (RBF) as the kernel function. The method was applied to predict t...A method of multiple outputs least squares support vector regression (LS-SVR) was developed and described in detail, with the radial basis function (RBF) as the kernel function. The method was applied to predict the future state of the power-shift steering transmission (PSST). A prediction model of PSST was gotten with multiple outputs LS-SVR. The model performance was greatly influenced by the penalty parameter γ and kernel parameter σ2 which were optimized using cross validation method. The training and prediction of the model were done with spectrometric oil analysis data. The predictive and actual values were compared and a fault in the second PSST was found. The research proved that this method had good accuracy in PSST fault prediction, and any possible problem in PSST could be found through a comparative analysis.展开更多
GO methodology is a success-oriented method for system reliability analysis. There are components with multi-fault modes in repairable systems. It is a problem to use the existing GO method to make reliability analysi...GO methodology is a success-oriented method for system reliability analysis. There are components with multi-fault modes in repairable systems. It is a problem to use the existing GO method to make reliability analysis of such repairable systems. A new GO method for reliability analysis of such repairable systems with multifault modes was presented. Firstly, calculation equations of reliability parameters of operators which were used to describe components with multi-fault modes in reparable systems were derived based on Markov process theory. Then, this new GO method was applied in reliability analysis of a hydraulic transmission oil supply system( HTOSS) of a power-shift steering transmission at low and high speeds. Finally,Compared with fault tree analysis( FTA) and Monte Carlo simulation,the results show that this new GO method is correct and suitable for reliability analysis of repairable system with multi-fault modes.展开更多
基金Supported by the Ministerial Level Advanced Research Foundation(3031030)the"111"Project(B08043)
文摘A method of multiple outputs least squares support vector regression (LS-SVR) was developed and described in detail, with the radial basis function (RBF) as the kernel function. The method was applied to predict the future state of the power-shift steering transmission (PSST). A prediction model of PSST was gotten with multiple outputs LS-SVR. The model performance was greatly influenced by the penalty parameter γ and kernel parameter σ2 which were optimized using cross validation method. The training and prediction of the model were done with spectrometric oil analysis data. The predictive and actual values were compared and a fault in the second PSST was found. The research proved that this method had good accuracy in PSST fault prediction, and any possible problem in PSST could be found through a comparative analysis.
基金Technical Basis Projects of China's MIIT(No.2012090003)
文摘GO methodology is a success-oriented method for system reliability analysis. There are components with multi-fault modes in repairable systems. It is a problem to use the existing GO method to make reliability analysis of such repairable systems. A new GO method for reliability analysis of such repairable systems with multifault modes was presented. Firstly, calculation equations of reliability parameters of operators which were used to describe components with multi-fault modes in reparable systems were derived based on Markov process theory. Then, this new GO method was applied in reliability analysis of a hydraulic transmission oil supply system( HTOSS) of a power-shift steering transmission at low and high speeds. Finally,Compared with fault tree analysis( FTA) and Monte Carlo simulation,the results show that this new GO method is correct and suitable for reliability analysis of repairable system with multi-fault modes.