Fault Detection of Multiple Unmanned Ships
Abstract: This paper presents an innovative approach for the fault detection of multiple unmanned ships using a fuzzy logic-based model. As unmanned surface vessels (USVs) gain prominence in maritime operations such as surveillance, transportation, and environmental monitoring, ensuring their operational reliability becomes crucial. Faults in these vessels, whether related to sensors, actuators, or communication systems, can lead to significant operational disruptions and safety hazards. The proposed fuzzy model addresses these challenges by leveraging the strengths of fuzzy logic in handling the inherent uncertainties and imprecisions in maritime environments. By considering a wide range of operational parameters and environmental conditions, the model can detect and diagnose faults in real-time, providing timely alerts and reducing the risk of mission failure. Extensive simulations have been conducted to evaluate the performance of the proposed model under various fault scenarios, demonstrating its effectiveness and robustness. The results indicate that the fuzzy model can accurately identify different types of faults, even in the presence of complex environmental variables, making it a valuable tool for enhancing the safety and efficiency of unmanned maritime operations.
Submission Number: 233
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