The invention belongs to the technical field of battery detection, and particularly relates to a naked
battery cell defect detection method and device, and the method comprises the steps: 1, in a
pole piece processing flow, in an interval from the completion of a baking process to the start of a winding process, obtaining a
pole piece surface image after the completion of each process or a part of processes in the interval; step 2, applying a preset
alternating current to the
pole piece to obtain an
infrared thermal distribution image of the pole piece; 3, applying a preset direct-current
high voltage between the positive
electrode and the negative
electrode of the naked
battery cell to obtain an
infrared thermal distribution image of the naked
battery cell; 4, acquiring an X-
ray image of the naked battery
cell; and 5, inputting the obtained surface image of the pole piece, the obtained
infrared heat distribution image of the pole piece, the obtained infrared
heat distribution image of the naked battery
cell and the obtained X-
ray image of the naked battery
cell into a preset AI analysis model based on
deep learning, and outputting a defect detection result of the naked battery cell through the defect analysis model. According to the invention, the defect detection and identification precision and capability are improved.