Article
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Fault Diagnosis of Maritime Equipment Using an Intelligent Framework
Version 1
: Received: 1 August 2024 / Approved: 2 August 2024 / Online: 5 August 2024 (03:42:36 CEST)
How to cite: Mendonça, L.; Sousa, J. M. C.; Vieira, S. M. Fault Diagnosis of Maritime Equipment Using an Intelligent Framework. Preprints 2024, 2024080192. https://doi.org/10.20944/preprints202408.0192.v1 Mendonça, L.; Sousa, J. M. C.; Vieira, S. M. Fault Diagnosis of Maritime Equipment Using an Intelligent Framework. Preprints 2024, 2024080192. https://doi.org/10.20944/preprints202408.0192.v1
Abstract
The task of automatically and intelligently diagnosing faults in marine equipment is of great significance due to the numerous duties that shipboard professionals must handle. Incorporating automated and intelligent systems on ships allows for more efficient equipment monitoring and better decision-making. This approach has attracted considerable interest in both academia and industry because of its potential for economic savings and improved safety. Several fault diagnosis methods are documented in the literature, often involving mathematical and control theory models. However, due to the inherent complexity of some processes, not all characteristics are precisely known, making mathematical modeling highly challenging. As a result, fault diagnosis often depends on data or heuristic information. Fuzzy logic theory is particularly well-suited for processing this type of information. Therefore, this paper employs fuzzy models to diagnose faults in a marine pneumatic servo-actuated valve. The proposed fault diagnosis framework analyzes the discrepancy signals between the outputs of the fuzzy models and the actual process outputs. These discrepancies, known as residuals, help in detecting and isolating equipment faults. The fault isolation process uses an intelligent decision-making approach to determine the specific fault in the system. This method is applied to diagnose abrupt faults in a marine pneumatic servo-actuated valve.
Keywords
intelligent fault diagnosis; model-based fault diagnosis; fuzzy modeling; marine equipment
Subject
Engineering, Marine Engineering
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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