Continual contrastive reinforcement learning: Towards stronger agent for environment-aware fault diagnosis of aero-engines through long-term optimization under highly imbalance scenarios

已完结 20 由 Guodong Qu 发布于 2026/10/11 21:47:16

DOI:10.1016/j.aei.2025.103297
作者：Haoze Wu ,?Shisheng Zhong ,?Minghang Zhao ,?Xuyun Fu ,?Yongjian Zhang ,?Song Fu
文献类型：期刊论文
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Abstract：Although the stability of aero-engines is high, their failures can lead to catastrophic consequences. Due to the infrequent nature of faults, traditional data-driven fault diagnosis methods

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