Application of Artificial Intelligence Techniques for the Detection and Diagnosis of Faults in Control Systems: A Scientific Literature Review
Geku *
Department of Electrical and Electronic Engineering, Federal University Otuoke, Nigeria.
Diton
Department of Electrical and Electronic Engineering, Federal University Otuoke, Nigeria.
Adebayo Adeniyi D
Department of Electrical and Electronic Engineering, Federal University Otuoke, Nigeria.
*Author to whom correspondence should be addressed.
Abstract
Identifying and forecasting issues in engineering systems is an essential responsibility for maintaining dependable and effective functionality. Conventional approaches for identifying and forecasting issues typically depend on human examination of system information, which can be labour-intensive and susceptible to mistakes. Technological advancements, especially in computational learning and information analysis, have surfaced as significant instruments for streamlining error identification and forecasting methods. This document offers a summary of the uses of artificial intelligence in identifying and forecasting faults in engineering systems.
Keywords: Fault detection, fault prediction, Artificial Intelligence (AI), machine learning