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Study On Transporter Robot System For Electrolytic Copper Stripping

Posted on:2014-09-28Degree:MasterType:Thesis
Country:ChinaCandidate:F LinFull Text:PDF
GTID:2208330467951157Subject:Mechanical and electrical engineering
Abstract/Summary:PDF Full Text Request
With the advantages of environmental protection and energy saving, the permanent cathode copper electrolysis technology is the development direction of copper smelting. At present, technology innovation is great needed to replace the traditional starting sheet mainly used in domestic copper plant. However, the configuration of corresponding starting sheet is needed in the permanent cathode copper electrolysis process. As the relative equipment in traditional technology is integrated and dedicated unit. So the traditional equipment technology is difficult to directly transform into the available equipment in the permanent cathode copper electrolysis process. This paper is intended to realize the recycle of the permanent cathode copper electrolysis technology transformation by using the various modules divided according to different functions of the existing integrated devices. For this, it designed electrolytic copper stripping robot in this paper to achieve the coordination of transit between the various modules, increasing the flexibility of arrangement between the modules combination, improving the utilization of existing equipment and reducing the technological transformation cost, all of these are conducive to the promotion of new technology.Firstly, the paper analyzed the process of electrolytic copper stripping for the purpose of compact and flexible of equipment layout, meeting a certain amount of work efficiency and the requirements. Through comparative analysis to determine the structure of robot type and transmission scheme, meanwhile, designed corresponding balance structure according to the load characteristics and selected structure of the robot, which can not only reduce the drive torque and power of required joint, but also can improve its stability, prolong the working life and finally complete its selection of electric motor and gearbox in the structure design.Secondly, joint coordinate system of the electrolytic copper stripping robot was set up based on the D-H method. Kinematic equations were built through the relevant mathematical model derivation according to the characteristics of the robot specific configuration, using the Monte Carlo method obtained the workspace of the robot and then solved the Jacobian matrix. In addition, given the recursive formula based on Kane dynamics equations of electrolytic copper robot. In order to ensure the safety and stability of the electrolytic copper stripping robot, it used the finite element method to analyze and check the major parts.Then, for the purpose of both higher operating efficiency and ensuring the smooth movement of electrolytic copper stripping robot, the paper presents a method of optimal time-jerk trajectory planning based on the cubic spline curve, by using which can connect the key points to generate the origin trajectory. Established the optimization objective function in weighted coefficient method which both time and jerk were taken into account. Meanwhile, an improved adaptive genetic algorithm (IAGA) which is suitable for solving multi-constrains and multi-objective problem was designed. The simulation of living example was completed based on Matlab programming environment which compiled the IAGA program and introduced the specific parameters of electrolytic copper stripping robot. It proved that the optimal trajectory planning technic showed in this paper can effectively balance the contradictory between operating efficiency and motion stability.Finally, the hardware control system of electrolytic copper stripping robot is designed for the special requirements of the multi-axis linkage, using three steps control mode. The system is open, and has an friendly man-machine interface which is low cost and easy to operate...
Keywords/Search Tags:Electrolytic copper, Robot, Structural design, Trajectory planning, Genetic algorithm
PDF Full Text Request
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