Time-Scaling-Based Energy-Saving Optimization Method And Typical Application Study Of Robot Machining System

With the advantages of dexterous operation,high efficiency,high control precision and low operating cost,industrial robots are widely used in various processing and manufacturing industries,and the resulting robot processing systems play an important role in the intelligent transformation and upgrading of the manufacturing industry.However,the robot peocessing system has lots of energy consumption sources and influencing factors,and the mechanism and law of energy consumption are complex.At present,there are many pieces of research on the energy consumption of machine tool machining systems,but there are few researches on energy saving of robot processing systems.The research on the energy consumption model and energy-saving optimization method of robot processing systems is of great significance to promote the low-carbon design and operation of robot processing systems and green and intelligent development in manufacturing industry.Combining with the National Natural Science Foundation projects "Research on energy consumption dynamic characteristics and energy-saving optimization method of industrial robot multi-operation"(51705050)and "Basic theory and key technology of laser processing technology and system optimization for low carbon manufacturing"(51861165202),this paper conducts the energy-saving optimization method and typical application research of robot processing systems based on Time-Scaling technology.Firstly,to address the problem that it is difficult to calculate and optimize energy consumption of industrial robots with multi-energy consumption sources and complex characteristics,the mechanism and complicated rules of robotic energy consumption are disclosed in detail based on the in-depth investigations of electromechanical compositions and energy flow of the robot,while an integrated energy consumption model of the robot is constructed.Based on this,a structured decomposition way of robotic energy consumption is proposed and the computational complexity and modeling characteristics of each part of energy consumption are analyzed.Then a technological direction that the parameterized energy consumption model for processing tasks is established based on Time-Scaling technology is propsed.Further the principles and methods of modifying robotic trajectories and establishing task energy characteristic models based on TimeScaling technology are introduced.The energy optimality of trajectory modification and trajectory energy-saving optimization of processing based on Time-Scaling technology are investigated and analysed,while the energy-saving optimization directions of typical robot processing systems and associated jobs are proposed.Secondly,aiming at the high-performance trajectory planning problem of robotic milling of complex curves/surfaces under complex constraints,an energy-saving trajectory planning method of robotic milling is proposed.The task energy characteristic model of the robot milling system is established at the micro-element action level based on the Time-Scaling technology,then the initial energy-optimal B-spline feedrate curve(BFC)is planned under speed constraints.Based on this,a planning method is proposed to transform the constrained nonlinear trajectory planning of minimizing energy consumption into a minimal modification of the initial energy-optimal BFC based on constraints.Furthermore,combined with the handling method of coupling problems of BFC modification and B-spline callback modification mechanism,a minimization modification algorithm of the BFC,with a callback mechanism,is proposed.The performance of the proposed method and algorithm is evaluated and verified through case studies.Then,in order to solve the problem of high energy consumption and low energy efficiency in robotic laser welding of complex components,an energy-saving optimization method of robotic laser welding systems is proposed based on machining system redundancy,which comprehensively considers the optimization of workpiece layout poses,tool postures and redundant robotic configuration selections.Through the analysis of energy consumption characteristics of the robot,laser and chiller,a generalized objective model of energy consumption of welding a single part,which includes the action-level task energy characteristic model,is established based on welding process characteristics and robot programming modes.On this basis,a mathematical model of the problem of minimizing the optimal energy consumption of robot laser welding of complex components scheduled by the Time-Scaling technology is constructed.Furthermore,in order to improve the computational efficiency of energy consumption optimization,the energy consumption target is deconstructed into three characteristic objectives with low computational cost,and a multi-objective optimization method for solving energy consumption optimization problems based on the NSGA-II algorithm is proposed.Through a case analysis,the feasibility and effectiveness of the proposed energy-saving method and problem-solving method are verified.Finally,aiming at the energy-saving optimization problem of automated robotic polishing of a mass of complex curved surface parts,an integrated processing energy modeling and optimization method of automated robotic polishing system(ARPS)is proposed.Based on the Time-Scaling technology,a task energy characteristic model of robotic polishing cells is established at the workpiece level to quickly predict the polishing energy consumption of a specific workpiece task.Furthermore,an energysaving optimization method for an ARPS with complex polishing tasks is proposed,which integratedly considers robot motion planning and task scheduling,while the corresponding mixed integer nonlinear programming model is established.An adaptive genetic algorithm is adopted to solve the model.A case study is introduced to verify the effectiveness of the established energy consumption model and the proposed approach.