摘要
状态预知是进行状态维修决策的关键和难点问题.针对维修实践中比较典型的设备两阶段故障过程,利用延迟时间的概念和随机滤波理论,基于直到当前时刻的状态监测历史信息,建立了两阶段的状态预知模型.该模型克服了一阶段状态预知模型的缺陷和不足,不仅能够动态地预知被监测设备在故障延迟阶段的残余寿命,而且将同一故障过程的2个阶段紧密联系起来,更接近于描述设备的真实运行过程.通过在Matlab环境下对该模型进行仿真,验证了该模型的有效性.
State prediction is a critical and difficult problem in condition-based maintenance decision making. Aimed at the typical two-stage failure process of a piece of equipment in maintenance practice, a two-stage state prediction model was designed based on condition monitoring information obtained using the concept of delaying time and stochastic filtering theory. The model overcomes the deficiencies of a one-stage state prediction model. Not only did the model dynamically predict the residual useful life of monitored equipment in the failure delayir^g stage, but also the two stages of its failure process combined together gave a closer description of the real operating process of the monitored equipment. The model was simulated by Matlab and the results of the simulation proved the effectiveness of the model.
出处
《哈尔滨工程大学学报》
EI
CAS
CSCD
北大核心
2007年第11期1278-1281,共4页
Journal of Harbin Engineering University
基金
国家自然科学基金资助项目(70301002)
关键词
状态维修
残余寿命
预知
延迟时间
滤波
condition-based maintenance
residual usefu
life
delay time
filtering
