基于机器视觉的芯片电阻歪斜和偏移检测方法研究OA

In the electronics manufacturing industry,the skewing and misalignment of chip resistors significantly affect the performance of circuits and the reliability of entire electronic products.To enhance the precision and efficiency of detection,this study proposed an automated detection method based on machine vision.The method integrated Hu invariant moments and affine transformation techniques to improve the accuracy and robustness of detection,especially when there were significant variations in the position and orientation of the components.The research initially explained the principle of image matching based on Hu invariant moments and utilized these moments for template matching.Subsequently,it elaborated on the application of affine transformations in correcting chip resistor images,including translation,rotation,and scaling.The effectiveness of the proposed method was validated through experiments and applied in practical production.The results demonstrate that the method can effectively enhance the accuracy and robustness of chip resistor skewing and misalignment detection.Finally,the study discussed the limitations of the method and potential directions for future improvement,offering a new solution for high-precision detection of chip resistors in modern electronics manufacturing.