Research Article Infrared Thermal Images of Solar PV Panels for Fault Identification Using Image Processing Technique V. Kirubakaran , 1 D. M. D. Preethi, 2 U. Arunachalam, 3 Yarrapragada K. S. S. Rao, 4 Mansour K. Gatasheh, 5 Nasrul Hoda, 6 and Endalkachew Mergia Anbese 7 1 Centre for Rural Energy, The Gandhigram Rural Institute, Gandhigram, Dindigul, Tamilnadu, India 2 Department of Computer Science and Engineering, PSNA College of Engineering and Technology, Dindigul, Tamilnadu, India 3 Department of Mechanical Engineering, University College of Engineering-Nagercoil, Tamilnadu, Nagercoil, India 4 Department of Mechanical Engineering, Aditya College of Engineering, Surampalem, 533437 Andhra Pradesh, India 5 Department of Biochemistry, College of Science, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia 6 Department of Neurology, Henry Ford Health System, Detroit MI 48292, USA 7 Department of Civil Engineering, Ambo University, Ambo, Ethiopia Correspondence should be addressed to Endalkachew Mergia Anbese; endalkachew.mergia@ambou.edu.et Received 9 February 2022; Revised 22 March 2022; Accepted 30 March 2022; Published 8 June 2022 Academic Editor: V. Mohanavel Copyright © 2022 V. Kirubakaran et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Among the renewable forms of energy, solar energy is a convincing, clean energy and acceptable worldwide. Solar PV plants, both ground mounting and the rooftop, are mushrooming thought the world. One of the significant challenges is the fault identification of the solar PV module, since a vast power plant condition monitoring of individual panels is cumbersome. This paper attempts to identify the panel using a thermal imaging system and processes the thermal images using the image processing technique. An ordinary and thermal image has been processed in the image processing tool and proved that thermal images record the hot spots. Similarly, the new and aged solar photovoltaic panels were compared in the image processing technique since any fault in the panel has been recorded as hot spots. The image recorded in the aged panels records hot spots, and performance has been analyzed using conventional metrics. The experimental results have also been verified. 1. Introduction The usage of renewable energy is increasing daily to give a sus- tainable and clean form of energy. The recent day’s use of solar energy has grown tremendously. Both rooftop and ground- mounted technologies penetrated the market at a rapid phase. In the same way, the operation and maintenance of solar panels also need to be taken care of. Solar PV systems are maintenance-free; however, the system’s monitoring is essen- tial to achieve the maximum yield from the plants. Several parameters affect the panel output like dust, humidity, shadow temperature, and moisture. In an extensive power plant, mon- itoring of individual panels is a cumbersome process. How- ever, any parameters affecting the yield of solar panels will induce internal resistance. Thus, a thermal image of the panels will be able to identify the fault of the panel quickly. Several thermal imagers are readily available in the market; analyzing individual images is a difficult task. Hence, the picture taken in a thermal imager is processed by MATLAB Simulink software for the different steps in the images’ layering. The temperature difference is associated with bordering the modules, and hot spots are easily identified. 2. Literature Review Different types of solution for the fault detection and the analysis by the various steps such as monitoring systems, I and C analysis based on artificial intelligence, and voltage and current measurements and also by power loss measure- ments analysis process of the different methods have no Hindawi International Journal of Photoenergy Volume 2022, Article ID 6427076, 10 pages https://doi.org/10.1155/2022/6427076