Research On Layout And Path Planning Of Automobile Parts Laser Cuttin

In the field of automobile intelligent manufacturing,the production process of automobile includes the packing of automobile parts and the cutting of the parts after the packing.The problem of packing of automobile parts refers to the study of how to compact the parts on the board,which can greatly improve the utilization rate of the plate.After parts packing,it is necessary to use laser to cut the packed parts,and a reasonable cutting path should be sought before cutting.This problem mainly refers to laser cutting path planning.The purpose of studying this problem is to improve the efficiency of laser cutting and realize automatic processing of automobile parts.In thesis,relevant solving strategies and intelligent optimization algorithms are proposed to solve these two problems,and on this basis,the automobile irregular parts packing and cutting path planning system is implemented.Main work:(1)Aiming at the problem of automobile parts packing,this thesis proposes an improved immune genetic algorithm to solve this problem,which combines the advantages of both genetic algorithm and immune algorithm.In order to prevent the algorithm from falling into local optimization prematurely,the individual concentration calculation is added to the genetic selection operation of the algorithm and an adaptive strategy is designed to adjust the relevant parameters and execution steps of the genetic algorithm.In addition,the convergence ability of the algorithm is improved by adaptive calculation the number of immune selection and cloned individuals.Polygon data set provided by ESICUP website and actual automobile parts data set are selected to test the algorithm,and the test results are compared with some existing literature results.The final test and comparison results show that the algorithm proposed in this thesis can achieve higher material utilization rate in most cases.(2)Aiming at single laser cutting path planning,a quantum immune algorithm is proposed to solve the cutting sequencing problem of parts.The immune selection,cloning,mutation and cloning suppression operators of the immune algorithm are introduced into the quantum evolutionary algorithm to improve the local search ability of the algorithm.In this thesis,polygon sample data provided by ESICUP and actual automobile parts data are also selected to test the proposed algorithm,and the test results are compared with the results of traditional intelligent optimization algorithm.Experimental results show that the proposed algorithm can improve the local search ability of quantum evolutionary algorithm,reduce the empty travel of laser cutting effectively,and improve the efficiency of laser cutting.(3)In order to further improve the efficiency of laser processing,the double laser cutting path planning problem was studied,and the fuzzy clustering vaccine immune algorithm was proposed to solve the problem.In this method,the path planning of double laser cutting is solved in two steps.In the first step,the fuzzy C-means clustering algorithm is used to assign cutting tasks to two laser heads,and then the path planning of double laser cutting is transformed into two single laser cutting path planning.In the second step,vaccine immune algorithm is used to solve the cutting and sequencing problem of parts.This algorithm introduces vaccination operation on the basis of immune algorithm to improve the global optimization ability of immune algorithm.Finally,relevant data sets are also selected to test the algorithm.The test results show that the proposed algorithm can approximately evenly distribute cutting tasks and improve cutting efficiency.Moreover,the planned empty travel paths of two laser heads do not cross,which can effectively avoid the problem of mutual interference between two laser heads when cutting.(4)According to the algorithm proposed in this thesis for solving the problem of auto parts packing and laser cutting path planning,the auto irregular parts packing and cutting path planning system is realized.The system is developed based on QT platform and uses C++ language.