Research Of Motion Control Network Based On Vision In Fast Testing And Sorting Of Solar Cells

Motion control network based on vision is an important part of industrial automation,it is also an important problem widely studied in the field of intelligent equipment,it integrates many subjects such as image processing,pattern recognition,automatic control and so on.With the continuous updating of computer technology,the expanding field of the intelligent control the continuous improvement of the level of industrial production,visual detection and motion control network has been developed rapidly,compared to the manual detection in high accuracy and high speed field,it has better advantages and is widely used in many fields,such as workpiece defect detection,robot etc..Solar cell is an important research object of the new energy industry,extensive research cells leading to rapid test cell sorting equipment constantly updated and improved,making the motion control network technology based on vision has become a research hotspot in cell production and scientific experiments.However,this technique needs to be developed further,it is shown in the following aspects:(1)The traditional artificial visual method has the disadvantages of low precision and slow efficiency,and the detection standard is easily affected by the workers’ supervisor,and it can not work uninterrupted for a long time.(2)Compared with foreign countries,the domestic testing equipment of solar cell is not good enough in terms of stability and automation level,so it will cost a lot to import foreign equipment directly.Therefore,the research of motion control network system based on vision is the main goal of this paper and to make it better for solar cell rapid testing and sorting equipment,its main characteristic is the combination of the visual detection and motion control network,the former is used to detect the surface defect and to extract the deflection angle and offset distance of the solar cell,through the latter,the parameters are sent to the motion control module to complete the correction of the solar cell and transfer to the test room for electrical performance testing.In order to realize high precision solar cell defect detection and efficient motion control network data transmission,the research contents include:(1)To study the cell shape and position correction parameter extraction,the deflection angle of cell placement and migration distance parameters,firstly by using Gauss filtering and edge detection algorithm to extract the cell contour edge and the main gate line edge,and then to calculate the deflection angle and the offset distance by the Hough transform.(2)Study of cell surface defect detection algorithm based on low rank decomposition,an imprecise augmented Lagrange multiplier method is used to decompose the defective image of the solar cell into a defective image and non-defective image.(3)According to deterministic real-time requirements of multi axis coordinated motion control of network transmission in the electric test,a network communication scheme based on time slot partition is proposed.First,an improved clock synchronization algorithm is used to complete the clock synchronization of nodes in the network,then according to the time slot partitioning strategy,tasks are scheduled,threads are created for each task,and the execution of threads are triggered by time and events,so as to improve network transmission performance.In this paper,the correction parameters of the cell shape and position are calculated and the surface defect image is extracted by algorithm processing.In order to test the performance of network communication,a two axis following platform is built,the experimental results show that the performance of clock synchronization is reliable,the two axis following effect is good,and the network transmission has good deterministic and real-time performance.