To address these problems, this paper proposes an IDETR deep learning target detection model based on Deformable DETR combined with transfer learning and a convolutional
View Details
For defect detection in crystalline silicon photovoltaics, the industry currently widely uses technologies such as manual visual inspection, current-voltage (I-V) curve analysis, infrared thermal imaging,
View Details
To address the current limitations of low precision and high image data requirements in defect detection algorithms based on visible light imaging, this paper proposes a novel visible light
View Details
As global solar capacity approaches 10 TW by 2030 (2024 Renewable Energy Market Report), surface defect detection has become mission-critical. This article breaks down the latest international
View Details
Power output will decline when foreign objests covered on PV panels. In this paper a system dsigned to detect the power output decline caused by foreign objests in different situations effectively.
View Details
This paper designed and implemented a detection system of foreign objects coverage on PV panels which mainly composed by power detection module, irradiance detection module, temperature...
View Details
To tackle this challenge, we propose an Adaptive Complementary Fusion (ACF) module designed to intelligently integrate spatial and channel information.
View Details
In order to detect photovoltaic panels in some special environments, a part of the dataset is selected for image processing, and the photovoltaic panel scene in some special scenarios is simulated by
View Details
The adoption of each of the reviewed techniques depends on several factors, including the deployment scale, the targeted defects for detection, and the required location of defect analysis in
View Details
The invention provides a photovoltaic panel foreign matter detection cleaning method and device, and aims to solve the technical problem that when a cleaning machine cleans a photovoltaic panel, the
View DetailsPDF version includes complete article with source references. Suitable for printing and offline reading.
