基于光谱分析和SVM的综合传动故障诊断研究

油液光谱分析是研究综合传动运行状态的重要方法，文章以油液光谱分析数据为基础，运用支持向量机(support vector machine，SVM)，建立了一种多输出最小二乘支持向量回归方法。利用多输出最小二乘支持向量回归方法对两台综合传动光谱油液分析数据进行了研究分析。研究表明，此方法得到的回归数据对1号综合传动试验数据具有良好的逼近效果，对2号综合传动油液光谱分析数据的预测具有较高的准确性。通过与2号综合传动试验数据的对比分析，发现了故障信息，并确定了故障部位。试验结果表明，该方法对于发现故障隐患，判断故障部位具有重要实际意义。

Study on Fault Diagnosis of Power-Shift Steering Transmission Based on Spectrometric Analysis and SVM

Spectrometric oil analysis is an important method to study the running state of Power- Shift Steering Transmission (PSST). A method of multiple out least squares support vector regression was developed using spectrometric oil analysis data and SVM(Support Vector Machine). The spectrometric oil analysis data were studied using multiple out least squares support vector regression. It has been proved that the regression data are good in approximation effect for No.1 PSST. And the predictive values for No.2 PSST are highly veracious with the test data. The fault information was found and the fault position was determined through comparative analysis. This method has been proved to have practice significance for finding fault-hidden dangers and judging fault positions.