Research On Free-form Surface Inspection Path Planning Based On Intelligent Algorithms

Free-form surface parts are currently used in a wide range of industries including aerospace,automotive,mould and die,biomedicine and optics,so the inspection of the geometry and accuracy of the free-form surface parts becomes critical.Coordinate measuring machines(CMMs)have been widely used in various industries for geometric measurement and inspection because of their high accuracy and ease of operation.As the measurement points on a free-form surface are inspected sequentially by the CMM,the point picking strategy and the measurement point path planning strategy are two important factors that affect the inspection accuracy and efficiency of the CMM.This paper investigates different intelligent algorithms to optimise free-form surface inspection paths as a means of improving the efficiency of free-form surface inspection.The following work has been done in this paper to optimise the free-form surface inspection path:(1)The Halton sequence sampling strategy is used to sample free-form parts at 50,100,200 and 400 scales,and the composition of the free-form surface inspection path and its corresponding mathematical model are also analysed.(2)Three different basic intelligent algorithms(simulated annealing algorithm,genetic algorithm,ant colony optimisation algorithm)are used to optimise the inspection paths of free-form surfaces.An optimised sequence of sampling points is obtained by simulating the free-form inspection path in MATLAB software using the three basic intelligent algorithms,and the free-form part is then inspected on a Leitz Reference HP bridge CMM according to the resulting sequence of sampling points.Based on simulations and example experiments,it has been shown that when optimising small-scale measurement points using all three conventional intelligent algorithms,short lengths of optimised paths can be obtained,thus improving the inspection efficiency of the CMM..However,as the three different basic intelligent algorithms have their own strengths and weaknesses,the optimisation results are not the same,i.e.the optimisation process and optimisation time as well as the optimised paths are not the same for the three basic intelligent algorithms.Based on the results of simulations and experimental examples,it can be seen that the ant colony optimisation algorithm has better optimisation results for path optimisation of free-form surfaces.(3)To further improve the inspection efficiency of free-form surfaces using CMM,this paper proposes a free-form CMM inspection path optimization method based on an improved ant colony optimisation algorithm.The inspection path composition and its mathematical model are first analysed,and then the improved ant colony optimisation algorithm is applied to minimize the objective function.To address the problem that the basic ant colony optimisation algorithm is difficult to jump out of the local optimal solution,the basic ant colony optimisation algorithm is improved by introducing a negative feedback mechanism in terms of pheromone update,which can obtain shorter measurement paths with higher probability.Experiments showed that the inspection path length optimised by the improved ant colony optimisation algorithm was at least 5.2% and8.6% shorter than those of the basic ant colony optimisation and simulated annealing algorithms,respectively.(4)To address the problems of long run time,long path length,and low efficiencies of basic intelligent algorithms to optimize free-form surface inspection path algorithms,this paper proposes a method based on an improved cuckoo search algorithm.Since the basic cuckoo search algorithm suffers from problems such as low search efficiency and the tendency to fall into local optimum solutions,the basic cuckoo search algorithm is improved by using a parameter adaptive adjustment strategy and dynamic neighbourhood search strategy,so that the improved cuckoo search algorithm can obtain the optimised inspection path stably and quickly.The local composition of the free-form surface inspection path and the corresponding mathematical model are first analysed,and then basic intelligent algorithms and the improved cuckoo search algorithm are applied to optimise the mathematical model.The results of inspection experiments conducted with an engine impeller showed that the improved cuckoo search algorithm reduced the length of the optimised inspection path by at least 8.6%,reduced the algorithm run time by at least35%,and improved the inspection efficiency by at least 1.2% compared to those of the genetic algorithm,simulated annealing algorithm,and ant colony Optimization algorithm.The improved cuckoo search algorithm allows for effective free-form surface inspection path Optimization and an improved inspection efficiency.