Optimization of Defect Detection Algorithm for Printed Circuit Board Based on Digital Twins
In view of the poor real-time monitoring performance and insufficient detection accuracy in the process of defect detection on traditional production lines,a digital twins-based algorithm for defect detection is proposed.Firstly,based on the operating characteristics of the detection equipment and the requirement of real-time monitoring,a basic framework for digital twins is proposed.Secondly,taking the visual inspection robot in the assembly line of microelectronic products as an example,a digital twins system for the robot is constructed based on the digital twins framework.Finally,leveraging knowledge in deep learning,the defect detection algorithm is optimized.Experimental results demonstrate that the improved algorithm achieved an accuracy rate of 96.5%,enhancing the intelli-gence level of visual detection and providing new insights for the intelligent management of robots.
国家科技期刊平台
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