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Design Of Automatic Spraying System Based On Machine Visio

Posted on:2023-10-09Degree:MasterType:Thesis
Country:ChinaCandidate:X Y WangFull Text:PDF
GTID:2531306833965019Subject:Control engineering
Abstract/Summary:PDF Full Text Request
Driven by "industry 4.0" and "made in China 2025",the competition in the field of industrial spraying is becoming increasingly fierce.People not only pursue products with higher level of automation and digitization,but also put forward higher requirements for its appearance.At present,the spraying industry still faces the problems of low productivity,high cost and unstable spraying quality;besides,its operation relies on skilled workers to a great extent.As for traditional spraying system needs to re-teach the spraying track when meeting different type of workpieces,which can lead to low level of automation and high consumption of human resources.In order to solve the above problems,we have designed an automatic spraying system based on machine vision.The system can make up for the existing shortcomings of the spraying industry and realize the task of spraying in complex environment.Our work will help small spraying enterprise realize stable transformation toward higher level of automation,quality and efficiency.The main work are as follows:1.We introduced machine vision to traditional spraying system and designed a new automatic spraying system based on machine vision,according to the problems of low spraying efficiency,unstable quality and unstable workpiece posture.The spraying system mainly composes of spraying robot module,vision module,transmission module and RFID module.We have completed the selection and design of each module.Although the automatic spraying system takes a lamp as the spraying object,it can be applied to the spraying of other types of workpieces.2.The orientation and dimension measurement of lamp workpiece are studied.Firstly,the most suitable algorithm is determined by comparison to preprocess the image;Then the canny edge detection algorithm is used to extract the edge of the workpiece,and the intersection of the main axis and secondary axis with the edge is taken as the feature point.According to the feature point,the transformation parameters are obtained for template matching;Finally,the camera calibration is used to locate the workpiece,and the measurement system is used to measure the workpiece size.All those work provides guarantee for spraying trajectory planning.3.According to the minimum circumscribed rectangle at the edge of the workpiece,a Z-shaped spraying along the long side square is proposed with the vertex of the minimum circumscribed rectangle as the starting spraying point,which can significantly improve the spraying efficiency.The triangulation method is studied,and the trajectory optimization problem of particle swarm optimization algorithm based on cross mutation is proposed.Due to the large amount of calculation and complex process of complex surface segmentation method,this thesis proposes a segmentation method for plane lamp workpiece to ensure the full coverage of coating.In this thesis,by establishing the growth rate model of spray gun and coating,taking the coating uniformity as the optimization objective and the variance between the actual coating thickness and the ideal coating thickness as the optimization function,the optimal solution is found,and the coating overlap distance and spraying speed at the best spraying effect are determined.4.Before coming into service,the system needs spraying simulation experiment.The spraying workstation is built in robot Studio software and the layout is determined.The lamp model established in Solidworks software is imported into the spraying workstation,and the spraying trajectory planning program is loaded into the controller for spraying simulation experiment.At the same time,the workspace and spraying trajectory of the spraying robot are simulated to verify the feasibility of the spraying system.
Keywords/Search Tags:spraying robot, Machine vision, Trajectory optimization, Automatic spraying system
PDF Full Text Request
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