基于GA-SVR的交流接触器剩余电寿命预测

Residual Electrical Life Prediction of AC Contactors Based on GA-SVR

为了解决交流接触器剩余电寿命预测中存在的特征选取单一和预测精度较低的问题,提出基于遗传算法优化支持向量回归(GA-SVR)的预测模型。首先,利用搭建的交流接触器全寿命测试平台采集电压电流信息,从中提取有效表征运行状态的特征参量。然后,采用近邻成分分析计算特征重要度,结合皮尔逊相关系数后选择出最优特征子集。最后,将交流接触器的剩余开断次数作为寿命预测标签,通过GA-SVR方法对交流接触器剩余电寿命进行回归预测。实例分析表明,所提方法准确率较高,能够满足实际工程需要。

In order to solve the problems of single feature selection and low prediction accuracy of residual electrical life prediction of AC contactor,a prediction model was proposed based on genetic algorithm support vector regression(GA-SVR).Firstly,the voltage and current information was collected using the AC contactor full-life test platform and the feature parameters which can characterize the operation state effectively were extracted.Then,the neighborhood component analysis was used to calculate the feature importance,and the optimal feature subset was selected combining with the Pearson correlation coefficient.Finally,the residual breaking times of the AC contactor were used as the life prediction label,and the residual electrical life of the AC contactor was predicted by the GA-SVR method.The case analysis shows that the method has a high accuracy and can meet the actual engineering needs.