基于退化数据和故障数据的设备维修决策模型

Zezhou Wang, Yun-xiang Chen, Zhongyi Cai, Huachun Xiang, Zheng Chang
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引用次数: 0

摘要

本文利用退化数据和故障数据对设备进行维修决策。首先,根据设备的退化数据,采用维纳过程建立退化模型;然后,根据设备的故障数据估计出故障阈值的随机分布系数,并推导出设备剩余使用寿命(RUL)分布的解析表达式。最后,根据更新奖励理论和RUL预测数据建立维修决策模型,实现设备的最优维修策略。仿真实例表明,该方法可以延长设备的运行时间成本,有效缩短设备的生命周期,具有广阔的应用前景。
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Equipment Maintenance Decision Model Based on Degradation Data and Failure Data
The degradation of data and failure data is used to make the maintenance decision of equipment in this paper. Firstly, the Wiener process is used to build the degradation model which is according to the degradation data of the equipment. Then, the random distribution coefficient of failure threshold is estimated by the failure data of the equipment, and we also derive the analytical expression of the remaining useful lifetime (RUL) distribution of the equipment. Finally, the maintenance decision model is established according to the renewal-reward theory and RUL prediction data which can achieve optimal maintenance strategy of equipment. The simulation example shows that the method in this paper can prolong the run time cost of equipment and effectively reduce the life cycle which has broad application prospects.
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