摘要：Maintenance management of devices is fundamental to ensure the supply reliability of natural gas pipeline system. A descriptive model integrating the state transition with the degeneration process of units was established. Then a method for calculating the maximum gas supply capacity of the pipeline system under scenarios of unit failure was developed. The maintenance strategy optimization model with a high supply reliability and a low maintenance cost was established, and a deep reinforcement learning-based method of maintenance optimization for the pipeline system was presented. The results show that compared with the scheduled maintenance, the proposed preventive maintenance strategy can improve the supply reliability and reduce the system maintenance costs. The average supply reliability increases from 99.41% to 99.54%, and the maintenance cost is reduced by 9.38%. ? 2023 University of Petroleum, China. All rights reserved.

ISSN号：1673-5005

卷、期、页：卷47期1：134-140

发表日期：2023-02-01

期刊分区（SCI为中科院分区）：无

收录情况：EI（工程索引）

发表期刊名称：Zhongguo Shiyou Daxue Xuebao (Ziran Kexue Ban)/Journal of China University of Petroleum (Edition of Natural Science)

通讯作者：范霖,Peng, Shiliang,张丽

第一作者：苏怀,张劲军

论文类型：期刊论文

论文概要：范霖,苏怀,Peng, Shiliang,张丽,张劲军，Supply-reliability based method of intellectual optimization on preventive maintenance strategy for natural gas pipeline system，Zhongguo Shiyou Daxue Xuebao (Ziran Kexue Ban)/Journal of China University of Petroleum (Edition of Natural Science)，2023，卷47期1：134-140

论文题目：Supply-reliability based method of intellectual optimization on preventive maintenance strategy for natural gas pipeline system