针对复杂装备故障信息不足、故障预测困难等问题,应用支持向量机建立了故障预测模型;在对支持向量机回归算法分析的基础上,利用最小二乘支持向量机建立故障预测模型;最小二乘支持向量机通过对相空间重构,有效地降低了模型的复杂度;最后,本文利用某导弹发射装置液压泵的故障数据进行了验证,通过选取合适的参数,该模型能够较好地对故障数据进行预测,预测精度较高;事实证明,基于最小二乘支持向量机建立故障预测模型能够较好地对复杂装备故障的趋势进行预测.%For the problems of not enough fault information for the complicated equipment and hard to predict the fault、 we apply Support Vector Machine (SVM) to build the fault prediction model. On the basis of analyzing regression algorithm of SVM, we use Least Square Support Vector Machine (LS-SVM) to build the fault prediction model. LS-SVM can effectively debase the complication of the model. Finally, we take the fault data of hydraulic pump in one missile launcher to validate this model. By selecting appropriate parameters, this model can make better prediction for the fault data, and it has higher prediction precision. It is proved that the fault prediction model which based on LS-SVM can make better prediction for fault trend of complicated equipment.
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