Photovoltaic cell panel inspection method based on deep learning
A photovoltaic panel and deep learning technology, applied in the field of power inspection and image processing, can solve the problems of unable to inspect the area of photovoltaic panels, unable to provide guarantee for the stable operation of photovoltaic substations, and unable to obtain the real status of equipment in time, etc., to achieve Effects of suppressing background interference, solving inspections, and improving robustness and accuracy
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[0046]The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention.
[0047] refer to Figure 1-3 , a photovoltaic panel inspection method based on deep learning, the steps are as follows:
[0048] Step 1: Prepare the network input data, use the drone to carry the imaging device to collect the image data set of the photovoltaic panel, including different damage types: damage, crack, cover, etc., all the image sizes are adjusted to eight 256pixel×256pixel, and then pass Labelme software labels the collected images with true value and outputs the labeled data set and the corresponding true value map;
[0049] Step 2: Enhance the data set by rotating, mirroring, scaling, and adjusting brightness to enrich the type and quantity of the data...
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