基于機(jī)器視覺(jué)的插件機(jī)研發(fā)
[Abstract]:With the development and progress of society, electronic products play a more and more important role in daily life, and plug-in machine is an indispensable equipment in the production line of electronic products. The plug-in machine replaces the traditional manual plug-in with the automatic plug-in, which greatly improves the efficiency of the plug-in and reduces the loss caused by human error. Therefore, both at home and abroad, plug-in machines have a very good development prospects. In this paper, the main parts of the plug-in machine based on machine vision are designed and analyzed, and the design of motion control system and image acquisition and recognition are completed. The motion control system of the plug-in machine is designed according to the requirements of the actual plug-in, and the main structure and technical specifications of the machine are determined. On the basis of understanding the working principle and working flow of the plug-in machine, the functions to be realized on each axis of the machine are determined, and then the mechanical analysis is done. According to the results of the analysis, the appropriate type of motor and driver are selected, and the peripheral circuit diagram is designed. After the motion control system is designed, the image acquisition system is designed. The image acquisition module is the core of the whole machine. In this paper, two kinds of structure design schemes are put forward, which are the image acquisition system based on the mobile camera and the image acquisition system based on the fixed camera. The calibration method is designed for these two structures. The calibration of machine is a bridge between machine and camera. The method and precision of calibration directly determine the accuracy of machine. The calibration methods based on fixed camera and mobile camera are introduced, and the feasibility of the method is verified by multiple plug-in experiments. The image acquisition module can collect images and process them. The algorithms used in image processing are divided into component recognition and Mark point recognition. The recognition algorithm of components includes pin recognition and contour recognition. Mark point recognition is firstly analyzed by Blob and then circle fitting is done by least square method. In addition, this paper proposes an image enhancement algorithm based on gray value quadratic linear transformation, which can achieve better preprocessing effect. After the above work, the prototype can be debugged and tested, including image processing precision experiment, mechanical precision test experiment, plug-in speed test experiment and so on. The experimental results show that the machine can meet the design requirements.
【學(xué)位授予單位】:哈爾濱工業(yè)大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2017
【分類號(hào)】:TP391.41
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