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Advanced thermal vision techniques for enhanced fault diagnosis in electrical equipment: a review

Author

Listed:
  • A. Sasithradevi

    (Vellore Institute of Technology)

  • J. Persiya

    (Vellore Institute of Technology)

  • S. Mohamed Mansoor Roomi

    (Thiagarajar College of Engineering)

  • D. Arumuga Perumal

    (National Institute of Technology Karnataka)

  • P. Prakash

    (Anna University, MIT Campus)

  • M. Vijayalakshmi

    (Vellore Institute of Technology)

  • L. Brighty Ebenezer

    (Vellore Institute of Technology)

Abstract

Ensuring the reliability and safety of electrical equipment is essential for industrial and residential applications. Traditional fault diagnosis methods involving physical inspections are time-consuming and ineffective for early fault detection. Infrared (IR) thermography offers a non-invasive and efficient solution by identifying anomalies in temperature profiles. This review explores thermal vision-based fault diagnosis techniques, including region of interest (ROI) segmentation, image pre-processing, and fault diagnosis algorithms, with a focus on deep learning approaches. The study highlights the effectiveness of machine learning models in enhancing fault detection accuracy while identifying challenges such as environmental variations, data inconsistencies, and system integration issues. The review discusses the role of real-time applications, wireless technologies, and AI-based automation in improving fault detection. Research gaps are identified, and future directions are proposed to enhance efficiency, reliability, and industrial adoption.

Suggested Citation

  • A. Sasithradevi & J. Persiya & S. Mohamed Mansoor Roomi & D. Arumuga Perumal & P. Prakash & M. Vijayalakshmi & L. Brighty Ebenezer, 2025. "Advanced thermal vision techniques for enhanced fault diagnosis in electrical equipment: a review," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 16(5), pages 1914-1932, May.
    • Handle: RePEc:spr:ijsaem:v:16:y:2025:i:5:d:10.1007_s13198-025-02782-9
    DOI: 10.1007/s13198-025-02782-9
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    References listed on IDEAS

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    1. Siddique Akbar & Toomas Vaimann & Bilal Asad & Ants Kallaste & Muhammad Usman Sardar & Karolina Kudelina, 2023. "State-of-the-Art Techniques for Fault Diagnosis in Electrical Machines: Advancements and Future Directions," Energies, MDPI, vol. 16(17), pages 1-44, September.
    2. Neeraj Khera & Shakeb A. Khan & Obaidur Rahman, 2020. "Valve regulated lead acid battery diagnostic system based on infrared thermal imaging and fuzzy algorithm," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(3), pages 614-624, June.
    3. Muhammad Rameez Javed & Zain Shabbir & Furqan Asghar & Waseem Amjad & Faisal Mahmood & Muhammad Omer Khan & Umar Siddique Virk & Aashir Waleed & Zunaib Maqsood Haider, 2022. "An Efficient Fault Detection Method for Induction Motors Using Thermal Imaging and Machine Vision," Sustainability, MDPI, vol. 14(15), pages 1-17, July.
    4. Deepam Goyal & Anurag Choudhary & B. S. Pabla & S. S. Dhami, 2020. "Support vector machines based non-contact fault diagnosis system for bearings," Journal of Intelligent Manufacturing, Springer, vol. 31(5), pages 1275-1289, June.
    5. Tang, Wuqin & Yang, Qiang & Dai, Zhou & Yan, Wenjun, 2024. "Module defect detection and diagnosis for intelligent maintenance of solar photovoltaic plants: Techniques, systems and perspectives," Energy, Elsevier, vol. 297(C).
    6. Ju Sik Kim & Kyu Nam Choi & Sung Woo Kang, 2021. "Infrared Thermal Image-Based Sustainable Fault Detection for Electrical Facilities," Sustainability, MDPI, vol. 13(2), pages 1-15, January.
    7. Srinivasan Alwar & Devakirubakaran Samithas & Meenakshi Sundaram Boominathan & Praveen Kumar Balachandran & Lucian Mihet-Popa, 2022. "Performance Analysis of Thermal Image Processing-Based Photovoltaic Fault Detection and PV Array Reconfiguration—A Detailed Experimentation," Energies, MDPI, vol. 15(22), pages 1-21, November.
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