Fault prediction of Power-Shift Steering Transmission based on support vector regression
Fault prediction of Power-Shift Steering Transmission based on support vector regression
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DOI：
10.1109/icinfa.2010.5512075
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发表时间：
2010-06
期刊：
影响因子：
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通讯作者：
Ying-feng Zhang;B. Ma;Jin-song Zhao;Hailing Zhang
中科院分区：
文献类型：
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作者：
Ying-feng Zhang;B. Ma;Jin-song Zhao;Hailing Zhang
油液光谱分析技术是状态监测的重要手段。本文将该方法应用于动力换档转向变速器的状态研究。但是，如何利用现有的数据来预测PST的未来状态是一项困难的工作。为了解决这一问题，采用了支持向量机回归方法。给出了该方法的建立过程。选择径向基函数(RBF)作为核函数。将该方法应用于油液光谱分析数据的研究。在此过程中，使用网格搜索法对参数γ和σ的取值进行了研究。并对石油光谱分析数据进行了预测。对预测值与实际值进行了对比分析。实践证明，该方法具有较好的预测精度，通过对比分析可以发现PSST中可能存在的任何问题，对预防故障具有重要意义。
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.