The invention provides a photovoltaic panel defect detection method based on
Raspberry Pi, and the method comprises the steps: exciting a to-be-detected photovoltaic panel through a
light source, and collecting a 16-frame original photovoltaic
image sequence through an
infrared focal plane array driven by an FPGA (
Field Programmable Gate Array); carrying out frame average
processing on the 16-frame original photovoltaic
image sequence to obtain a background mean value image; according to the original photovoltaic
image sequence and the background mean value image, calculating a deviation absolute value of a sample and a mean value by using a mean absolute error to obtain a deviation feature image representing defect information; de-noising
processing is carried out on the deviation characteristic image by adopting a selective multi-stage median filtering
algorithm and enhancement
processing is carried out on the deviation characteristic image by adopting a self-adaptive linear segmentation stretching
algorithm in sequence, so that a preprocessed
photoluminescence image is obtained; making a training
data set based on the preprocessed
photoluminescence image, and training the constructed ACF-YOLO
network model to obtain a photovoltaic defect detection model; and reasoning a to-be-detected image by using the photovoltaic defect detection model, and outputting a final photovoltaic module defect detection result. The invention solves the limitation of the existing
photoluminescence (PL) defect detection instrument.