AI-Driven Fault Diagnosis and System Resilience for Offshore Oil Drilling Platforms
DOI:
https://doi.org/10.54097/97cgpa14Keywords:
Fault diagnosis, system resilience, artificial intelligence, predictive maintenance.Abstract
Offshore oil platforms serve as a critical part of the global energy industry and thus work under high risk and complex environments. Severe accidents in the past have shown that the traditional, reactive methods of fault diagnosis are inadequate in terms of concerning the operational safety. The advent of Artificial Intelligence (AI) is leading to a great change of proactive and predictive models as a more effective way of managing these risks. Nevertheless, a holistic assessment between the diagnosis of fault and system resilience in modern contexts is not present. This article splendidly outlines how the process of diagnosis started with a rudimentary method to a modern and high-tech AI-based approach. Moreover, it presents, and discusses a critical concept of system resilience, specifically regarding solving mutual crises like physical equipment malfunctions and cyber-attacks. These concerns are designed to facilitate a proper picture of how these intelligent technologies in place can improve the safety and efficiency of offshore platforms.
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