基于红外图像的太阳能面板的缺陷检测

Defect Detection of Solar Panel Based on Infrared Image

由于太阳能电池板在使用过程中可能存在各种缺陷,因此,缺陷检测对确保太阳能发电的效益至关重要。本文提出了基于红外成像的缺陷检测方法,利用红外相机捕获太阳能电池板表面的温度分布图像,并通过图像处理和分析确定可能存在的缺陷区域。为进一步提高检测精度,本文采用了传统图像处理和卷积神经网络(CNN)相结合的方法,得到了更准确的缺陷检测结果。实验结果表明,该方法可以有效地检测出太阳能电池板表面的缺陷,并具有较高的准确率和较强的鲁棒性。

Due to various defects that may exist during the use of solar panels,defect detection is crucial for ensuring the efficiency of solar power generation.In this paper,a defect detection method based on infrared imaging is proposed.The infrared camera is used to capture the temperature distribution image of the solar panel surface,and the possible defect areas are determined through image processing and analysis.In order to further improve the detection accuracy,this paper uses the combination of traditional image processing and convolutional neural network(CNN)to obtain more accurate defect detection results.The experimental results show that this method can effectively detect defects on the surface of solar panels,and has high accuracy and strong robustness.