A Digital Twin Approach for Fault Diagnosis in Unmanned Ships Integrated Power System

L. Qi, S. Ruihao, Yan Xingang, Y. Moduo, Su Lei, H. Wentao
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Abstract

The Integrated Power System (IPS) of unmanned ship has integrated various equipment and thus has a complex structure. Current fault diagnosis approaches rely heavily on fault history data and case-by-case models, making it difficult for unattended operation. This paper proposes a model-free fault diagnosis method based on Digital Twin (DT) system. The rule-based discriminative approach is adopted to efficiently identify system faults and their type without the need for historical data or specific physical models. The unmanned ship IPS is modeled on the RTLAB hardware-in-the-loop simulation platform, and the DT system is established on Simulink. Case study about diagnosing the propulsion branch faults on unmanned ships is performed. The results show that the proposed method can quickly detect system faults accurately identify the specific damaged equipment.
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基于数字孪生的无人船综合动力系统故障诊断方法
无人船综合动力系统集成了多种设备,结构复杂。目前的故障诊断方法严重依赖于故障历史数据和个案模型,难以实现无人值守操作。提出了一种基于数字孪生(DT)系统的无模型故障诊断方法。采用基于规则的判别方法,在不需要历史数据或特定物理模型的情况下,有效地识别系统故障及其类型。在RTLAB硬件在环仿真平台上对无人船IPS进行建模,在Simulink上建立DT系统。对无人船推进支路故障诊断进行了实例研究。结果表明,该方法能够快速检测系统故障,准确识别出具体的损坏设备。
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