Condition Monitoring of Electric Machines: Modern Frameworks and Data-Driven Methodologies

Electrical machines are at the centre of most engineering processes, with rotating electrical machines, in particular, becoming increasingly important in recent history due to their growing applications in electric vehicles and renewable energy. Although the landscape of condition monitoring in electrical machines has evolved over the past 50 years, the intensification of engineering efforts towards sustainability, reliability, and efficiency, coupled with breakthroughs in computing, has prompted a data-driven paradigm shift. This paper explores the evolution of condition monitoring of rotating electrical machines in the context of maintenance strategy, focusing on the emergence of this data-driven paradigm. Due to the broad and varying nature of condition monitoring practices, a framework is also offered here, along with other essential terms of reference, to provide a concise overview of recent developments and to highlight the modern challenges and opportunities within this area. The paper is purposefully written as a tutorial-style overview for the benefit of practising engineers and researchers who are new to the field or not familiar with the wider intricacies of modern condition monitoring systems.

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Publication Details

Journal
Machines
Published
2025-02-13
DOI
https://doi.org/10.3390/machines13020144
Citations
5
Primary Topic
Machine Fault Diagnosis Techniques
Type
article
Field-Weighted Citation Impact
6.07
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article

Condition Monitoring of Electric Machines: Modern Frameworks and Data-Driven Methodologies

Wesley Doorsamy
5 citations
Machines
Machine Fault Diagnosis Techniques
6.07
article

Condition Monitoring of Electric Machines: Modern Frameworks and Data-Driven Methodologies

Wesley Doorsamy
article en
5 citations

Abstract

Electrical machines are at the centre of most engineering processes, with rotating electrical machines, in particular, becoming increasingly important in recent history due to their growing applications in electric vehicles and renewable energy. Although the landscape of condition monitoring in electrical machines has evolved over the past 50 years, the intensification of engineering efforts towards sustainability, reliability, and efficiency, coupled with breakthroughs in computing, has prompted a data-driven paradigm shift. This paper explores the evolution of condition monitoring of rotating electrical machines in the context of maintenance strategy, focusing on the emergence of this data-driven paradigm. Due to the broad and varying nature of condition monitoring practices, a framework is also offered here, along with other essential terms of reference, to provide a concise overview of recent developments and to highlight the modern challenges and opportunities within this area. The paper is purposefully written as a tutorial-style overview for the benefit of practising engineers and researchers who are new to the field or not familiar with the wider intricacies of modern condition monitoring systems.

MachinesVol. 13(2)
University of Leeds (GB)
Openalex Percentile: Top 4%
Machine Fault Diagnosis Techniques
6.07
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