Machine Learning Approaches for Fault Detection in Internal Combustion Engines: A Review and Experimental Investigation

Machine Learning Approaches for Fault Detection in Internal Combustion Engines: A Review and Experimental Investigation

Fault diagnostics in internal combustion engines (ICEs) is vital for optimal operation and avoiding costly breakdowns. This paper reviews methodologies for ICE fault detection, including model-based and data-driven approaches. The former uses physical models of engine components to diagnose defects,...

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Bibliographic Details
Main Authors: A. Srinivaas, N. R. Sakthivel, Binoy B. Nair
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Informatics
Subjects:
internal combustion engines
machine learning
classifiers
feature engineering
predictive modeling
supervised learning
Online Access:https://www.mdpi.com/2227-9709/12/1/25
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