不完美维护下基于剩余寿命预测信息的设备维护决策模型

基于剩余寿命预测信息进行设备维护决策的研究中，现有方法通常仅考虑不完美维护对退化量或退化率的单一影响，忽略了不完美维护对两者的双重影响.鉴于此，针对随机退化设备，提出一种考虑不完美维护影响的性能退化模型与维护决策模型，融合了维护活动对设备退化量和退化率的双重影响.首先基于Wiener过程分阶段构建存在不完美维护干预的随机退化模型，在首达时间的意义下推导出剩余寿命的解析概率分布；然后基于剩余寿命的预测结果，以检测间隔和预防性维护阈值为决策变量建立维护决策模型；最后数值仿真实验验证了本文模型的有效性，并对费用参数进行了敏感性分析.实验结果表明本文模型具有潜在的工程应用价值.

Remaining Life Prediction Information-based Maintenance Decision Model for Equipment Under Imperfect Maintenance

In making a maintenance decision for equipment based on remaining life prediction information, current methods normally consider that maintenance activities can only have influence on either the degradation level or the degradation rate, but not on both. In this paper a degradation model and a maintenance decision model considering the influence of imperfect maintenance for stochastic deteriorating equipment are proposed so as to combine the influences of imperfect maintenance activities on both degradation level and degradation rate. A stochastic degradation model subject to the intervention of imperfect maintenance is firstly established based on the multi-phase Wiener process, and the analytical probability distribution of the remaining life is derived in the sense of the first hitting time. Then, a maintenance decision model whose decision variables are the monitoring interval and the preventive maintenance threshold is constructed based on the remaining life prediction information. Finally, a numerical simulation is provided to substantiate the effectiveness of the proposed model and to analyze the sensitiveness of the cost parameters. The experiment result shows that the model has potential to be applied in practice.