A New Automatic Fault Diagnosis Algorithm for Electrical Equipment Based on Infrared Thermography

Date Received: Feb 11, 2025

Date Accepted: Jun 26, 2025

Date Published: Jun 28, 2025

DOI: https://doi.org/10.31817/vjas.2025.8.2.

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Issue: Vol. 8 No. 2 (2025): Vietnam Journal of Agricultural Sciences

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ENGINEERING AND TECHNOLOGY

How to Cite:

Truong, N., Hoc, N., Duong, N., & Tien, D. (2025). A New Automatic Fault Diagnosis Algorithm for Electrical Equipment Based on Infrared Thermography. Vietnam Journal of Agricultural Sciences, 8(2), 2509–2519. https://doi.org/10.31817/vjas.2025.8.2.

A New Automatic Fault Diagnosis Algorithm for Electrical Equipment Based on Infrared Thermography

Nguyen Xuan Truong 1 , Nguyen Thai Hoc (*) 1 , Ngo Tri Duong 1   , Dao Xuan Tien 1

  • Corresponding author: [email protected]
  • 1 Faculty of Engineering, Vietnam National University of Agriculture, Hanoi 12400, Vietnam

    • Keywords

    Thermal imaging, thermal image segmentation, thermal anomalies detection, power monitoring system, electrical equipment

    Abstract


    In this paper, a novel algorithm is proposed for an Efficient Fault Diagnosis Method (EFDM) for electrical equipment in real time. A combined optical and thermal image processing system is employed to detect thermal anomalies in electrical components in real time. A video camera is initially used to monitor and identify the electrical components, while an infrared camera, aligned with the same viewpoint, is used to capture thermal images of the equipment. The EFDM is then applied to identify and locate faults in electrical components. Numerical results indicate that the proposed algorithm achieves higher accuracy in detecting thermal anomalies compared to existing methods. Evaluation across 300 scenarios shows that the proposed method achieves 97.57% accuracy in localizing abnormal electrical components and 95.30% accuracy in estimating their surface temperatures. These results demonstrate that the proposed thermal anomaly detection algorithm is effective for electrical power monitoring applications.

    Author Biographies

    Nguyen Xuan Truong, Faculty of Engineering, Vietnam National University of Agriculture, Hanoi 12400, Vietnam

    Truong Xuan Nguyen received his B.Sc and M.Sc degrees in electrical and electronic engineering from Vietnam National University of Agriculture, Vietnam in 1995 and 2002, respectively. He then received PhD degree in Electric Power Systems at the College of Energy and Electrical Engineering, Hohai University, Nanjing 210098, China in 2012. His research interests include wind power system. 
    He can be contacted at: [email protected]@vnua.edu.vn.

    Nguyen Thai Hoc, Faculty of Engineering, Vietnam National University of Agriculture, Hanoi 12400, Vietnam

    Hoc Thai Nguyen is Lecture and Researcher at Vietnam National University of Agriculture, Hanoi, Vietnam. He received his B.Sc and M.Sc degrees in electrical and electronic engineering from Vietnam National University of Agriculture, Vietnam in 2006 and 2010, respectively. He then received PhD degree in infocommunication technologies and Automation at the Budapest University of Technology and Economics (BME), Hungary in 2018. His research interests include wireless sensor networks, Internet of Robotic Things and Applications of Artificial Intelligence in Precision Agriculture. He can be contacted at email: [email protected]; [email protected].  

    Ngo Tri Duong, Faculty of Engineering, Vietnam National University of Agriculture, Hanoi 12400, Vietnam

    Duong Tri Ngo received the PhD degree in Control Engineering and Automation from Hanoi University of Science and Technology, Vietnam, in 2009. He is currently a senior lecturer at the Faculty of Engineering of VNUA. His main research interests are control systems, IoT, and AI applications for smart agriculture. He can be contacted at: [email protected].

    Dao Xuan Tien, Faculty of Engineering, Vietnam National University of Agriculture, Hanoi 12400, Vietnam

    Tien Xuan Dao received the MA degree in electrical engineering and electrical system from the Vietnam National University of Agriculture (VNUA), Vietnam, in 2010. He is currently a lecturer at the Faculty of Engineering of VNUA and a PhD candidate at Hanoi University of Science and Technology (HUST), Vietnam. His research interests include control systems, smart grids, and AI applications for smart agriculture. He can be contacted at: [email protected].

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