In the production of new energy batteries, the quality of electrode coating is crucial. WeLinkirt's 3D point cloud fusion technology provides an effective solution for online full inspection of electrode coating.
User scenario: A leading new energy battery manufacturer needs to conduct online full inspection of electrode products on the electrode coating production line. As the core component of the battery, the coating quality of the electrode directly affects the performance and safety of the battery. Therefore, the inspection objects are the key indicators such as the surface quality and dimensional accuracy of the electrode coating.
Pain points: Traditional inspection methods have many problems. In terms of quantification, it is difficult for human eyes to standardize and quantify the appearance criteria. Different inspectors have different judgments on the size, color, and surface grading of the electrodes, resulting in frequent missed detections and false alarms. For example, in the detection of surface defects, the missed detection rate of manual inspection is relatively high, and some small scratches, bubbles and other defects are easily overlooked. At the same time, manual inspection is inefficient, requiring a large amount of manpower, and the model change time is long, which cannot meet the needs of large-scale production. In addition, with the improvement of industry standards, the compliance requirements for electrode inspection are becoming more and more stringent, and traditional inspection methods are difficult to meet these requirements.
Technical principle
WeLinkirt's 3D point cloud fusion technology combines advanced algorithms and hardware devices. In terms of imaging, a self-developed 3D camera is used to obtain the three-dimensional morphology information of the electrode, and the surface features of the electrode are presented in the form of point clouds through the three-dimensional morphology reconstruction technology. In terms of algorithms, the feature recognition ability of the visual basic model is used to analyze and identify various features of the electrode. For example, for the size detection of the electrode, the length, width, height and other dimensional parameters of the electrode can be accurately calculated through the point cloud data; for the surface defect detection, the semantic false alarm filtering algorithm can effectively distinguish real defects from interference factors and improve the accuracy of detection. This technology is effective because the 3D point cloud fusion can provide more comprehensive and accurate electrode information, avoiding the limitations of traditional 2D detection, and the advanced algorithm can efficiently process and analyze complex point cloud data.
- The three-dimensional morphology reconstruction technology can accurately restore the surface morphology of the electrode, providing a basis for subsequent detection and analysis.
- The feature recognition ability of the visual basic model can quickly identify various features of the electrode, improving the detection efficiency.
- The semantic false alarm filtering algorithm can effectively filter false alarm information and improve the accuracy of detection.
- The comprehensiveness and accuracy of the point cloud data make the detection results more reliable.
WeLinkirt's solution and product introduction
WeLinkirt provides the DaoAI AI AOI software system and the DaoAI 2D / 3D AI AOI equipment. The DaoAI AI AOI software system has a powerful feature recognition ability of the visual basic model, which can realize zero-code automatic programming within 5 minutes for a good product. Through the APDT positive sample/few-sample learning (only 1-20 good products are needed), an accurate detection model can be quickly established. At the same time, the semantic false alarm filtering function can effectively reduce false alarms. The DaoAI 2D / 3D AI AOI equipment uses a self-developed 3D camera and combines the three-dimensional morphology reconstruction technology, which can detect hidden solder joints, coplanarity, and micron-level morphology, providing high-precision hardware support for electrode coating inspection. In terms of implementation, the equipment is installed on the electrode coating production line, and the software system collects and analyzes the point cloud data obtained by the 3D camera in real time to realize online full inspection of the electrodes.
WeLinkirt's solution brings efficient and accurate inspection methods for the inspection of new energy battery electrode coating.
Quantitative results: By adopting WeLinkirt's solution, the new energy battery manufacturer has achieved significant results. The detection rate of electrode coating defects has reached 98.5%, effectively reducing the missed detection rate and ensuring the quality of the electrodes. The false alarm rate has been reduced by -65%, reducing unnecessary re-inspection and manual intervention. The model change time has been shortened from several hours to 5 minutes, greatly improving the production efficiency and meeting the needs of large-scale production.