Ying-feng Zhang

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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(More)
—Based on the mathematical model of wet clutch engagement, a dynamic model of a tracked vehicle was developed by means of the software Matlab/Simulink. This model can be used to simulate the shift schedule, piston pressure and relative velocity. A two dimensional heat conduction model was also developed with reasonable selection of proper boundary(More)
Fault pattern recognition is an important work in condition monitoring of Power-Shift Steering Transmission (PSST). Spectrometric oil analysis technology is a common and useful method to study the state of PSST. But, how to find the implicit information in data and classify the running state is a difficult work. In order to solve this problem, a support(More)
Support vector machine (SVM) is an efficient method for data mining of oil analysis. The principle and structural risk of SVM are described in this paper. And the structural risk is studied using oil analysis data. During the process, parameters determination is a very important part because parameters have great influence on the performance of SVM. We(More)
—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 γ and σ 2. The selection of(More)
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