基于机器视觉的小型工件尺寸测量系统研究
[Abstract]:With the development of automation in machining industry, the traditional measurement technology can no longer fully adapt to the current development needs, and the machining industry also put forward higher requirements for the size measurement of machined workpiece. The small workpiece measurement system based on machine vision studied in this paper mainly solves the problems of slow manual measurement, easy fatigue in long time measurement, low measurement precision, and difficulty to realize measurement automation and so on. In this paper, the hardware scheme of the system is determined according to the need of the project, and the working principle of the main hardware such as camera, lens and light source is analyzed. In order to highlight the contour boundary of the measured workpiece and avoid the reflection of the surface of the metal workpiece, the LED ring shadowless light source is selected to illuminate the contour of the workpiece. In addition, the specific models of the camera, lens and other hardware equipment are determined, the whole hardware platform of the measurement system is constructed, and the camera calibration and the image photographing of the measured workpiece are completed. Using Matlab 8.0 to develop the program, the whole process is divided into five main parts. The first is image filtering, after comparison and analysis, the median filtering algorithm is used to filter the partial noise in the image without destroying the edge information of the workpiece. The second is image binarization. In this system, histogram threshold method is used to determine the threshold value, and the edge and background of the image are clearly distinguished. Third, image edge extraction, the system uses the Canny operator for edge extraction, effective extraction of image edge information, including the real edge information of the workpiece and noise edge information. Fourth, the edge of noise is eliminated. In this part, a binary image continuous bright spot region aggregation algorithm is proposed. Firstly, each edge pixel, including noise edge pixel and workpiece effective edge pixel, is aggregated in each set, and then the number of pixels between the noise edge and the effective edge of the workpiece is different from the number of pixels between the noise edge and the effective edge of the workpiece. Finally, the real edge of the workpiece can be extracted effectively by judging and eliminating the noise edge points. Fifth, the edge segment fitting, this paper proposes a mapping segmentation algorithm, this algorithm uses the image inflection point before and after the coordinates of the slope difference is large to find the edge of the inflection point, accurate and effective realization of the continuous edge segmentation. Finally, the edges involved in this paper are mainly straight lines and arcs, which are fitted directly by straight lines and circles, and then the length of each edge is obtained to complete the measurement work. From the experimental results, it can be seen that the small workpiece measurement system based on machine vision designed in this paper can realize real-time, automatic and high-precision measurement.
【学位授予单位】:西南交通大学
【学位级别】:硕士
【学位授予年份】:2017
【分类号】:TG806;TP391.41
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