一种面向健康状态预测的设备维护方法

Equipment Maintenance Method Based on Health State Prediction

针对国有资产经营管理中如何以较小的人力物力投入达到设备最优工况的问题,提出一种面向设备健康状态预测的维护方法:将设备的历史维护数据作为输入信息,通过支持向量机(SVM)算法构建的预测模型获得输出结果,根据预测结果建立设备健康状态评价等级及相应的维护措施,以实现国有资产设备的健康状态评价及状态准确预测,从而制定科学的维护计划,达到尽可能减少故障发生、延长设备服役时间的目的,最终实现国有资产的保值和增值,本文以天津市某国有资产经营管理为例,初步实现了设备的故障预测与健康管理,助力实现设备“状态修”的转型。

Aiming at the problem of how to achieve the optimal working condition of equipment with small human and material resources investment in the operation and management of state-owned assets,a maintenance method for equipment health state prediction is proposed:take the historical maintenance data of equipment as the input information,obtain the output results through the prediction model constructed by Support Vector Machine(SVM)algorithm,and establish the evaluation level of equipment health state and corresponding maintenance measures according to the prediction results,in order to realize the health state evaluation and accurate state prediction of state-owned assets and equipment,so as to formulate a scientific maintenance plan,achieve the purpose of minimizing the occurrence of faults and prolonging the service time of equipment,and finally realize the preservation and appreciation of state-owned assets.Taking the operation and management of a state-owned asset in Tianjin as an example,the failure prediction and health management of equipment have been preliminarily realized,helping to realize the transformation of equipment state repair.