Analysis And Optimization Of Fixture Layout Based On Discretization And Genetic Algorithm

With the rapid development of automation control technology,high-efficiency precision machining technology has also made a big leap,but the processing quality problem is still plagues its progress,A workable fixturing layout is prerequisite to guarantee safety?precision and efficient processing.For this purpose,the method of kinematics contact mechanism should be studied to predict and control the optimal model of fixturing layout to minimize the position deviation of the workpiece.This paper analyzes the main factors affecting the machining accuracy in the workpiece-fixture system,namely the local deformation(including the deformation of the clamping element and the contact deformation between the workpiece and the clamping element).It also reveals the relationship between the local deformation caused by the contact reaction force and the positional deviation of the workpiece,and describes thechanges situation to the positions of the workpieces in various directions over time.Offset situation.Based on the contact simulation of the workpiece-fixture linear spring-damping system,combined with the particle position transformation technology and energy conservation principle in the vibration system,the kinematics equation of the position deviation of the workpiece and its one-way contact constraint conditions were constructed.The optimal model of fixturing layout is used to realize the prediction of workpiece position deviation,and the control of the workpiece position offset value is minimized by the genetic algorithm optimization method.When solving a reasonable clamping layout model,based on the general genetic algorithm technology,the surface of the element to be planned is discretized into a finite set of points,and the node information data under stable fixturing is invoked by MATLAB software,and genetic iteration operation is performed one by one to.The automatic optimization design of the fixture layout has greatly improved the convergence efficiency,and the efficiency of the analysis example is 65.8% higher than the time spent by the general genetic algorithm.At the same time,Taguchi Orthogonal Test Method is used to set the value of each key parameter in the discretization genetic algorithm,and the influence of the grid size of different length on the optimization result is discussed,which provides a criterion for the selection of this parameter and a basic theory for CAFD application design.Because of the disadvantages of general genetic algorithm,which is easy to fall into local convergence and the slow speed of convergence,a cellular genetic algorithm based on the principle of cellular automata is proposed.The interaction between individual cells occurs in the domain of the spatial grid.It is beneficial to expend and enrich the diversity of populations,and uses a complex multi-peak test function F to verify the advantages of the method when searching for the global optimal solution.and applies this technique to solving the best fixture layout,obtaining a better convergence effect,which provides a new guidance method of fixturing layout design for the complex workpieces.