Hot spot fault detection method for photovoltaic cell panel

The invention discloses a hot spot fault detection method for a photovoltaic cell panel, and belongs to the field of fault detection of a photovoltaic power generation system. The method comprises the steps: collecting infrared images in different hot spot fault states; carrying out the preprocessing and segmenting of the infrared images, and extracting a hot spot fault characteristic vector; training an SVM multi-fault detection model, and optimizing the parameters in the SVM through employing PSOM; and finally building a hot spot fault detection model for the photovoltaic cell panel. The method achieves the hot spot fault detection of the photovoltaic cell panel, gives a hot spot damage level, provides precise hot spot fault information, and prompts the safe and effective operation of the photovoltaic power generation system. 本发明公开了种光伏电池板热斑故障检测方法，属于光伏发电系统故障检测领域。首先通过采集不同热斑故障状态下的红外图像，对红外图像预处理并分割提取热斑故障特征向量，然后训练SVM多类故障检测模型，并采用PSOEM优化SVM中的参数，最终建立光伏电池板热斑故障检测模型，实现对光伏电池板的热斑故障检测，并给出热斑损伤等级，从而提供精确的热斑故障信息，促进光伏发电系统的安全有效