基于最小二乘支持向量机的复杂装备故障预测模型研究  

Research on Fault Prediction Model of Complicated Equipment Based on Least Square Support Vector Machine

作　　者：连光耀 吕晓明[2] 黄考利 孙江生 

机构地区：[1]军械技术研究所,河北石家庄050003 [2]军械工程学院,河北石家庄050003

出　　处：《计算机测量与控制》2011年第5期1030-1032,共3页Computer Measurement &Control

基　　金：国家自然基金资助项目(60771063)

摘　　要：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.

关 键 词：故障预测模型 回归算法 最小二乘支持向量机 

分 类 号：TP206[自动化与计算机技术—检测技术与自动化装置]