A method for recognizing positive and negative electrodes of buzzer circuit board based on machine vision

In order to automate the soldering of coils to circuit boards in buzzers, this study proposes a method for recognizing positive and negative electrodes of buzzer circuit board based on machine vision. The method distinguishes and locates the positive and negative electrode of the circuit boards, which facilitates subsequent soldering operations. Since buzzer circuit boards are left-right symmetric and the positive and negative solder pads are highly similar in morphology, it is difficult to distinguish between the positive and negative electrodes based on visual features. The method first employs the color difference operator R-G-B to extract the color feature map of the circuit board. Next, algorithms such as filtering, threshold segmentation and contour detection are employed to extract the circuit board contours, and the rotated minimum bounding rectangle of each circuit board is obtained to achieve precise locating. Then, according to the up-down asymmetric geometric characteristics of the circuit boards, the positive and negative electrode recognition problem is converted into a simple geometric analysis problem. According to the current orientation of the circuit board, it is categorized into eight cases, and corresponding calculation formulas of positive and negative position are designed, effectively distinguishing and locating the positive and negative electrodes of the circuit board. Experimental results demonstrate high recognition accuracy of the method: The error in extracting the minimum bounding rectangle is only single-digit(zero to ten) pixel values. Finally, the average relative error in recognizing the positive and negative electrode positions is less than 2%. Tests confirm that the proposed method achieves robust recognition and locating performance, showing promising potential for application in automatic soldering equipment to realize automated soldering of buzzer circuit boards.