Project Challenges
Complexity of Defect Types: The project faces a wide range of defects, including false soldering, desoldering, reverse assembly of electrode groups, deformation of electrode terminals, bending of busbars, and abnormal number of electrode tabs. This diversity of defects increases the complexity of detection.
Variety of Defect Materials: Defects in different materials manifest in various forms, further escalating the difficulty of detection.
Absence of Industry Standards: The lack of unified industry standards results in ambiguous defect boundaries, making it difficult to determine whether a product is defective based on clear data.
Continuous Emergence of New Defects: During production, new types of defects constantly arise, placing high demands on the adaptability of detection technology.
Equipment Limitations and Positional Offsets: The equipment at the site has certain limitations, and the position of the products to be inspected often shifts, affecting the accuracy of detection.
Solutions
To address these challenges, we have implemented the following solutions:
Establishment of the Qingzhe Platform: By building a business process on the Qingzhe platform, we can efficiently manage and streamline the detection workflow.
Algorithm Reuse for Different Defects: For various defect types, we reuse positioning and segmentation algorithms. Through extensive learning of defect features, we achieve precise identification and deliver high-quality detection results.
Implementation Effects
The implementation of these solutions has led to significant improvements:
Low Missed Detection Rate: The missed detection rate has been reduced to 0.01%.
Controlled Over-detection Rate: The over-detection rate does not exceed 5%.
These achievements effectively ensure the quality inspection of battery products, demonstrating the effectiveness and reliability of our solutions.
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