## 1 Introduction  
Renewable energy aims to be a reliable power supply, offering fuel diversification, maintaining energy security, minimizing the risk of fuel spills, and lowering the demand for imported fuels. Nowadays, there are numerous domains of application that utilize renewable energy sources, such as medical [1], driverless cars [2], and wireless wearables [3]. As a renewable energy source, solar energy produces solar power, converted into electricity--i.e., solar cells, also called photovoltaic cells that convert sunlight into electricity [4, 5]. The authors of [7, 8] suggest that photovoltaic (PV) gets its name from the process of converting light (photons) to electricity (voltage), through a process called the photovoltaic effect. Solar panel technology boasts many advantages and is a cost-effective alternative to or extension of power sources for both urban and rural applications [9, 10, 11]. As described above, PVs are based on photo-radiation absorption and conversion in a range of wavelengths. Heat (i.e., infrared) is emitted from the PV panels during power conversion. This heat dissipation process and the heat emitted by an object, or a person can be captured and recorded using a thermal camera [12, 13]--the use of which is increasing in different monitoring applications in fields such as engineering [14, 15], structural systems [16, 17], security [18, 19], and medical fields [20, 21]. Moreover, a thermal camera can help to highlight hazardous areas radiating temperatures beyond their normal operating limits, the overheating on an electrical system, and related abnormalities in machines. As shown in Figure 1, the corresponding thermal image of an actual gas pipe taken using our thermal camera shows the temperature (\({}^{\circ}\)C) variations between the gas pipe and its surrounding environment.  
If thermal imaging techniques are to be utilized in PVs, the early detection of defects would be manageable. Images acquired using an infrared camera are transformed into visible images by assigning a variant of color to each infrared energy level and showing its corresponding temperature differences. The need to diagnose a photovoltaic system is necessary, which can provide a monitoring mechanism to determine the health condition of the solar panel module. The IR camera can present an even heat distribution for a healthy solar panel, while uneven heat load for a degrading one because of uneven temperature distribution.  
The main objective of this study is to examine the importance of a thermal camera for fault diagnosis, which can correlate to the solar panel's thermal signature in assessing the health conditions of the solar panels. The acquired thermal solar panel images were processed using the developed algorithm to provide detailed information on the solar panel's health status, which is helpful for solar panel assessment. Specifically, to highlight the cumulative distributive function (CDF) as one important parameter when dealing with image processing for assessing/evaluating the health condition of solar cells/panels. In addition, a cross-validation scheme uses a convolutional neural network (CNN) method for automatic classification of whether the image to be tested is on a defective category or not. The rest of this paper is organized as follows: Section 2 highlights how thermal imaging technology is used in photovoltaic systems. Section 3 describes the proposed algorithm. Simulations, testing, and evaluation results are presented in Section 4. Finally, Section 5 concludes this study.