Abstract
This paper focused on the condition monitoring problem of the Power-Shift Steering Transmission (PSST). Spectrometric oil analysis is an important way to study the running state of PSST. Because of complicated nonlinear relationship in oil analysis data, a model of PSST’ fault classification based on v- Support Vector Machine (v-SVM) is proposed. The fundamental of v-SVM is researched. The influence of model parameters for performance of v-SVM is analyzed. Experimental results show that, comparing with C-support vector machine and BP neural network, the v-support vector machine has good properties in research of fault classification of PSST.
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Acknowledgments
This work was funded by the Defense Advanced Research Support Project of the CPLA General Equipment Department under grant no. 62301030303.
Funding of this research has been provided by School of Mechanical Engineering, Beijing Institute of Technology. We appreciate the advice of our colleagues.
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Zhu, Y., Zhang, Yf., Du, Ay. (2013). Study on Fault Classification of Power-Shift Steering Transmission Based on v-Support Vector Machine. In: Qi, E., Shen, J., Dou, R. (eds) The 19th International Conference on Industrial Engineering and Engineering Management. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38433-2_70
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DOI: https://doi.org/10.1007/978-3-642-38433-2_70
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