基于机器视觉的芯片快速识别定位系统的设计与实现—电路和控制系统设计

location system based on machine vision--the design of circuitand control systemAbstractWith the development of science and technology,the development trend ofmicroelectronic components is also towards miniaturization.The identification of chipdefects has many consequences caused by traditional manual detection.Not only isthe labor cost high,but the efficiency cannot be mentioned.The high precisionrequired cannot be guaranteed.Today's chip inspection industry has high standards,high speeds,and high precision.Traditional inspection methods have also exposedvarious shortcomings.It will become a trend that chip recognition systems based onmachine vision will gradually replace traditional inspections,and it is quite importantto study this design.Because using machine vision to detect the chip does not need todirectly touch the chip under test,and has the advantage of working for a long time.Due to the non-contact nature of the detection process,unnecessary influence factorscan be avoided during the detection process,thereby improving the detectionaccuracy.Using machine vision technology to detect the specific parameters of thechip can solve the various shortcomings brought by the traditional manual detection,and it is more scientific.Therefore,in recent years,China has gradually appliedmachine vision technology to chip recognition test systems.In this paper,through the identification and detection process of chip products,the circuit and control system of chip rapid recognition positioning system based onmachine vision are designed.The hardware equipment of a chip recognition system isextremely important,such as industrial cameras,lenses,and light sources.The qualityof the hardware determines the imaging quality.The camera of this design is triggeredby PNP photoelectric sensor.The obtained chip image is calculated by the machinevision algorithm.Finally,a visual human-computer interaction interface is designedby the Visual Studio 2017 platform.Data and processing time of the chipKeywords:machine vision;chip recognition system;industrial camera;human-computer interaction interface;Visual Studio 2017目录