The Inspection System Of Board Chip Pin Soldering Defects Based On Machine Vision

With the rapid development of the electronics industry, the demand of integrated circuit board is increasing dramatically. How to detect manufactured products fast and efficiently has attracted the attention of the enterprises. It is inevitable that the visual inspection method will replace the manual detection methods. However, in practical applications, targeted objects have different characteristics, it is necessary to design corresponding system to different objects.The targeted board is the main component of signal receiver which is used to accept signal form electronic key of automobile. Since the antenna and the antenna bracket have been assembled on the board, the existing integrated circuit board inspection equipment cannot be used to detect such integrated circuit chip directly. As a result, the mainly detect method is manual inspectionthrough optical magnifier. Based on the space projection theory, this paper determined the effective detecting spatial location and optimized the moving trajectory, designed an inspection system to detect the soldering defects of this type of circuit board by machine vision.This paper adopted the machine vision inspection method to detect the soldering defects of integrated circuit boards with antenna, introduced the composition and working principle of the inspection system, designed a visual inspection experimental system to satisfy the technical requirements of user.The research includes three aspects.1. Summarized chip soldering defects detection and visual detection methods. Proposed a non-contact detection method based on machine vision detection to adjust the chip space orientation, and verified the feasibility of this method by experiment.2. Designed the structure of the machine vision inspection for the soldering defects of this integrated circuit board chip, including the hardware part and the software part, and the path of movement.3. According to the user detection requirements, developed the detection strategies software, which accomplish the machine vision inspection to detect soldering defects for such board by VisualC++ 6.0 and MFC.