Analysis and Evaluation of Pre-processing Techniques for Fault Detection in Thermal Images of Solar Panels

Pathak, Sujata; Patil, Sonali A.

doi:10.1007/978-981-19-5482-5_59

Cited by 1 publication

(1 citation statement)

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“…Local preprocessing refers to a method that uses a small neighborhood of pixels in the input image to generate new brightness values in the output image, such as smoothing filtering, sharpening filtering, edge detection, etc. [51]. These methods can remove noise or other small fluctuations, or enhance detail or edge information in an image.…”

Section: Overlay Detection Technology Based On Image Processingmentioning

confidence: 99%

A Survey of Photovoltaic Panel Overlay and Fault Detection Methods

Yang,

Sun,

Zou

et al. 2024

Energies

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Photovoltaic (PV) panels are prone to experiencing various overlays and faults that can affect their performance and efficiency. The detection of photovoltaic panel overlays and faults is crucial for enhancing the performance and durability of photovoltaic power generation systems. It can minimize energy losses, increase system reliability and lifetime, and lower maintenance costs. Furthermore, it can contribute to the sustainable development of photovoltaic power generation systems, which can reduce our reliance on conventional energy sources and mitigate environmental pollution and greenhouse gas emissions in line with the goals of sustainable energy and environmental protection. In this paper, we provide a comprehensive survey of the existing detection techniques for PV panel overlays and faults from two main aspects. The first aspect is the detection of PV panel overlays, which are mainly caused by dust, snow, or shading. We classify the existing PV panel overlay detection methods into two categories, including image processing and deep learning methods, and analyze their advantages, disadvantages, and influencing factors. We also discuss some other methods for overlay detection that do not process images to detect PV panel overlays. The second aspect is the detection of PV panel faults, which are mainly caused by cracks, hot spots, or partial shading. We categorize existing PV panel fault detection methods into three categories, including electrical parameter detection methods, detection methods based on image processing, and detection methods based on data mining and artificial intelligence, and discusses their advantages and disadvantages.

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Section: Overlay Detection Technology Based On Image Processingmentioning

confidence: 99%