Can yolov5 detect laser welding defects of a lithium battery pole?

Aiming to solve the rapidly expanding demand for detecting laser welding defects of a lithium battery pole, we developed a YOLOv5-based algorithm as an image analysis module for the AOI system. We did not use the officially provided pre-training weights, and all network models were trained from scratch.

Is there an automatic weld defect detection method based on faster R-CNN?

Min-jae Jung et al. [ 16] proposed an automatic weld defect detection method based on the Faster R-CNN algorithm to address the problem of manual and costly weld quality inspection in the shipbuilding industry.

Why is it important to monitor welding defects?

Welding quality plays a vital role in the durability and effectiveness of welding structures. Therefore, it is essential to monitor welding defects to ensure welds quality. Manual inspection, analysis and evaluation of welding defect images is difficult due to the non-uniformity in their shape, position, and size.

What happens after welding lithium battery tabs?

After the welding process of Lithium battery tabs, it is necessary to detect the surface defects of the welded products. The Gap is one of the common defects, a

Why do we need deep learning to identify welding defects?

Manual inspection, analysis and evaluation of welding defect images is difficult due to the non-uniformity in their shape, position, and size. Hence the use of deep learning techniques to identify welding defects is more accurate and reliable due to the adequate training data samples, which helps to identify welding defects with greater accuracy.

Why is laser welding used in lithium ion batteries?

Laser welding is widely used in lithium-ion batteries and manufacturing companies due to its high energy density and capability to join different materials. Welding quality plays a vital role in the durability and effectiveness of welding structures. Therefore, it is essential to monitor welding defects to ensure welds quality.