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Naval Ship Gas Turbine performance decline in service will raise the risk of operation, thus it is necessary to study the condition-based maintenance strategy for its degraded state in different degrees. Based on the Markov decision process and the maskable PPO algorithm, the maintenance environment model of Naval Ship Gas Turbine degradation state is constructed in the simulation environment, and the model adaptively finds the optimal maintenance strategy through training. Through the simulation experiment, it is verified that the condition-based maintenance strategy of Naval Ship Gas Turbine in a degraded state can be combined with the maskable PPO algorithm, and the maintenance cost of Naval Ship Gas Turbine can be well controlled during its service life.

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The Research of Naval Ship Gas Turbine Maintenance Decision Based on the Maskable PPO Algorithm

  • 会议论文

  • 发表日期：

    2025年

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  • Zhicai Zhou,
  • Tao Yu,
  • Zhilong Lin,
  • Mingjie Zhang,
  • Ruizhe Hao,
  • Zongqing Zhao,
  • Hanwei Xu

摘要

Naval Ship Gas Turbine performance decline in service will raise the risk of operation, thus it is necessary to study the condition-based maintenance strategy for its degraded state in different degrees. Based on the Markov decision process and the maskable PPO algorithm, the maintenance environment model of Naval Ship Gas Turbine degradation state is constructed in the simulation environment, and the model adaptively finds the optimal maintenance strategy through training. Through the simulation experiment, it is verified that the condition-based maintenance strategy of Naval Ship Gas Turbine in a degraded state can be combined with the maskable PPO algorithm, and the maintenance cost of Naval Ship Gas Turbine can be well controlled during its service life.