AI-Driven Predictive Maintenance for Electrical Machines and Systems

Artificial Intelligence (AI) is transforming the domain of electrical engineering by facilitating smart decisionmaking, predictive analytics, and automation in a vast variety of applications.This paper offers an exhaustive discussion of the adoption of AI methodologies like machine learning, deep learning, fuzzy logic, and evolutionary algorithms in prominent areas of electrical engineering such as power systems, smart grids, renewable energy, electrical machines, and power electronics.The research examines how AI improves system efficiency, reliability, and fault tolerance using intelligent load forecasting, predictive maintenance, adaptive control, and fault diagnosis.Additionally, the paper identifies current developments, recent achievements, challenges, and future directions in AI-based electrical engineering solutions.The results indicate that ongoing development and integration of AI can play an important role in the development of more sustainable, efficient, and smart electrical infrastructures.

Publication Details

Journal
IJIREEICE
Published
2025-06-19
DOI
https://doi.org/10.17148/ijireeice.2025.13619
Primary Topic
Machine Fault Diagnosis Techniques
Type
article
Field-Weighted Citation Impact
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article

AI-Driven Predictive Maintenance for Electrical Machines and Systems

IJIREEICE
Machine Fault Diagnosis Techniques
article

AI-Driven Predictive Maintenance for Electrical Machines and Systems

article en

Abstract

Artificial Intelligence (AI) is transforming the domain of electrical engineering by facilitating smart decisionmaking, predictive analytics, and automation in a vast variety of applications.This paper offers an exhaustive discussion of the adoption of AI methodologies like machine learning, deep learning, fuzzy logic, and evolutionary algorithms in prominent areas of electrical engineering such as power systems, smart grids, renewable energy, electrical machines, and power electronics.The research examines how AI improves system efficiency, reliability, and fault tolerance using intelligent load forecasting, predictive maintenance, adaptive control, and fault diagnosis.Additionally, the paper identifies current developments, recent achievements, challenges, and future directions in AI-based electrical engineering solutions.The results indicate that ongoing development and integration of AI can play an important role in the development of more sustainable, efficient, and smart electrical infrastructures.

IJIREEICEVol. 13(6)
Affordable and clean energy
Openalex Percentile: Top 84%
Machine Fault Diagnosis Techniques
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AI-Driven Predictive Maintenance for Electrical Machines and Systems · IJIREEICE (2025) | TGRS Research Map | TGRS