3C Electronics - Printed Circuit Board Inspection

Project Difficulties

Complex Detection Items: The production quality of PCB boards is crucial to the performance of electronic products. There are numerous detection items, including solder bridging, cold solder joints, open solder joints, and missing pins. Solder bridging can cause short - circuits in the circuit, cold solder joints may lead to poor contact during the product's use, open solder joints render the circuit connection ineffective, and missing pins directly affect the electrical connection of components. The diverse types of these defects increase the complexity and difficulty of detection.

Complex Characteristics of Detection Targets: The detection targets are not only extremely small in size but also vary in shape and are large in quantity. The tiny size poses extremely high requirements for the accuracy of the detection equipment. Different shapes require targeted detection algorithms, and a large number of targets mean that a massive amount of data needs to be processed. Any deviation in any link may lead to inaccurate detection results.

Difficulty in Unifying Lighting and Shooting Conditions: Due to the different specifications of PCB board products, it is difficult to control a lighting environment and shooting distance that are suitable for all products during actual detection. Different lighting intensities, angles, and shooting distances will all have a significant impact on the quality of image acquisition, thereby interfering with subsequent detection analysis and reducing the accuracy and stability of detection.

High Cost of Product Motion Control System: To achieve a comprehensive inspection of PCB boards, a product motion control system is required to assist the camera in multi - angle and all - round shooting. However, high - precision product motion control systems are expensive, which not only increases the upfront investment cost of the project but also poses a challenge to the project's economic benefits.

Solutions
The line - scan camera and multi - light - source imaging method are adopted, combined with the technology of deep learning and image algorithm fusion calculation to achieve accurate positioning of common defects on PCB boards. The line - scan camera can scan line by line with high resolution to obtain clear images of PCB boards. The multi - light - source illuminates the PCB boards from different angles and intensities, effectively highlighting the defect characteristics of different types. The deep - learning algorithm is trained with a large amount of sample data, continuously learning the characteristic patterns of various defects. The image algorithm is responsible for pre - processing and feature extraction of the collected images. The two are integrated with each other to jointly improve the detection accuracy. For complex defects, the deep - learning algorithm is continuously optimized during the production process, new defect samples are continuously accumulated, and the algorithm parameters are adjusted to gradually improve the direct recognition accuracy.

Implementation Effects
After practical application, this solution has achieved remarkable results. Monthly statistical data shows that the model recognition effect has reached an accuracy of 99.9%. This means that in a large number of PCB board detections, the vast majority of defects can be accurately identified, effectively ensuring product quality, reducing the defective product rate, and improving production efficiency and economic benefits.