Photovoltaic cell panel batch broken gate detection method and system based on artificial intelligence
A technology of photovoltaic panels and photovoltaic cells, which is applied in image data processing, instruments, calculations, etc., can solve the problems of missed detection and prone to false detection, and achieve the effect of eliminating the influence of different lighting
Inactive Publication Date: 2021-01-05
河南颂达信息技术有限公司
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[0003] In the existing industrial preparation process, the detection methods for surface broken grids mainly include detection methods using background modeling and manual visual detection methods. Due to the different image illumination of each panel and the influence of stains, it is very easy to Misdetection, missed detection, etc.
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[0051]In order to further explain the technical means and effects of the present invention to achieve the intended purpose of the invention, in conjunction with the accompanying drawings and preferred embodiments, an artificial intelligence-based photovoltaic panel batch broken grid detection method and The system, its specific implementation, structure, features and effects are described in detail as follows.
[0052]Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field of the present invention.
[0053]It should be noted that the ideal image of a photovoltaic panel is:
[0054]1. The grid lines are longitudinal thin lines that appear periodically;
[0055]2. The area between the grid lines is a pure color or single color area;
[0056]3. The ideal image of the photovoltaic panel only includes the gate line and the silicon crystal area. The pixel value of the gate line is the same, and the pixe...
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The invention provides a photovoltaic cell panel batch broken gate detection method and system based on artificial intelligence, and relates to the field of artificial intelligence. The method comprises the steps of obtaining an initial image of a single photovoltaic cell panel; obtaining a transverse relation spectrum by comparing difference values between pixels in each column of the same frameof the preprocessed initial image; counting difference values of the same positions in all the transverse relation spectrums, and establishing a template relation spectrum by using the difference values appearing most frequently in each position; and processing the template relation spectrum, establishing a grid line template image, taking the grid line template image as a mask, extracting grid line pixels in each frame of image, comparing difference values of single-row pixels of a single-frame image in the grid line pixels, establishing a fitting curve, and judging the position of a broken grid defect. According to the invention, the negative influence of illumination and stains on broken gate detection can be eliminated, broken gate detection is carried out on photovoltaic cell panels in batches at the same time, and the broken gate position is directly obtained.
Description
Technical field[0001]The invention relates to the field of artificial intelligence, in particular to a method and system for detecting batch broken grids of photovoltaic panels based on artificial intelligence.Background technique[0002]As a renewable clean energy, solar energy has been widely promoted in photovoltaic applications. At present, the scale of China's solar energy industry is developing rapidly, and it is an important producer of solar photovoltaic cells. As the carrier of solar power generation, photovoltaic panels are generally expected to have a longer service life and higher conversion rate. However, the grid-breaking defects that occur during the manufacturing process limit their applicability. Therefore, effective detection methods are very important to improve the quality of photovoltaic panels.[0003]In the existing industrial preparation process, the methods of detecting surface grid breakage mainly include the detection method using background modeling and the m...
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CPCG06T7/001G06T2207/30108
Inventor 曾强黄晨华
Owner 河南颂达信息技术有限公司