The invention discloses a
solar cell defect detection method based on a multi-mode sensing technology. The
system comprises the following steps: 1, multi-
modal data acquisition: acquiring multi-
modal data in real time by using four sensing technologies of near-
infrared laser, area array visible light, PL and EL; 2, multi-
modal data processing: carrying out denoising,
edge detection and
feature extraction on the acquired near-
infrared, visible light, PL and EL images by adopting a mixed
image processing algorithm to obtain key defect features; 3, multi-
modal data fusion: combining a multi-
modal data fusion method with a decision-making level strategy, synthesizing different technical data, improving the detection precision, and classifying, positioning and labeling the defects of cracks, broken gates, scratches, depressions, poor
welding and hot spots by using a
convolutional neural network to ensure accurate distinguishing of surface and internal defects; and 4, defect marking and
production line adjustment: marking defects and adjusting the
production line through a feedback and
automatic control module, and feeding back a real-time visual result to a management layer.