Research Of Image Processing And On-line Testing For Preparating Superfine-line Electrode

Because of increasingly serious energy crisis,solar energy as green,environmentally friendly energy has broader application prospects.So solar cell manufacturing technology has been received a lot of attention.3D electronic printing technology is now utilized in solar cell manufacturing field.The width of the positive silver gratings printed by this technology can reach 40 um.A special image detection system is needed to obtain clear images of the droplets,because of the small droplet volume.Based on the above problem,ultra-fine grating image process and on-line detection system are described by this thesis.At the beginning of this thesis the background and significance of this research are introduced.First,3D electronic printing technology and the research status of the manufacturing process of gratings are introduced.Then the advantages of the electronic technology in the process of manufacturing gratings is introduced.Finally,the overall structure of the article is introduced.Then the system design of the whole experimental platform is summarized.This part mainly includes three aspects,the composition of the ultra-fine grids jet-printing system,the composition of nano-silver particles micro drop precision injection control system and the composition of the drop image acquisition system.Then the data analysis and processing system about ultrafine grids is introduced.The main content is data parsing and transformation of prt documents,mainly including file parsing,data conversion technology based on multi nozzle array and the processing and Multi nozzle jet printing data processing system.Finally,the droplets image processing and detection system is introduced.The main content of this chapter is the droplet image processing method and on-line defect detection of ultra-fine grids.The first part contains the preprocessing method of droplet image,droplet grayscale image processing and the droplet image threshold segmentation and feature extraction.The second part includes droplet image acquisition and preprocessing,droplet image defects detection,the integrated design of function modules and algorithm and practical application cases.