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Aiming at the difficulty and low accuracy of manual defect detection of the dual-ball infrared receiver chip, a pin defect detection system based on machine vision is designed to detect the pins of the dual-ball infrared receiver chip to distinguish normal Chips and defective chips. First, the chip image is collected in real time through an industrial camera, and preprocessing such as filtering and grayscale processing is performed; then the PMAlign tool of VisionPro vision software is used for image feature matching, the number of pins is calculated to determine whether the pins are missing, and the AnglePonitPonit tool is used to calculate Pin spacing to determine whether the pins are bent; Finally, the detected chip position information and recognition results are sent to the industrial robot through the socket communication protocol. According to the recognition result, the industrial robot grabs the normal chips and defective chips to different areas to realize the classification management of the chips. Experimental results show that the detection accuracy of the defect detection system reaches ±0.01mm, and the misjudgment rate is less than 0.5%, which meets the requirements of industrial production.