A Particle Swarm Optimization Algorithm Based on Beetle Antennae Search for Flatness Error Evaluation
LIU Chao1,WANG Chen1,2,ZHONG Yu-ning1
1. Hubei University of Automotive Technology, Shiyan, Hubei 442002, China
2. Shanghai Key Laboratory of Intelligent Manufacturing and Robotics, Shanghai 200072, China
Abstract：A particle swarm optimization algorithm based on the beetle antennae search algorithm (BAS-PSO) is proposed to evaluate flatness errors. Firstly, a mathematical model for evaluating the flatness error based on the minimum region is established and the objective function is transformed into a nonlinear optimization problem. Secondly, on the basic of particle swarm optimization algorithm (PSO), the beetle antennae search algorithm (BAS) with strong global search ability is introduced. As a result, the parallel computation of global search and local search is sped up to avoid premature convergence and falling into local optimization, and the accuracy and efficiency of flatness error evaluation is improved. Finally, the effectiveness of BAS-PSO is experimented by Rosenbrock and Schaffer test functions, BAS-PSO is used to solve the objective function based on the evaluation mathematical model of flatness error of the minimum region, the experimental results show that the algorithm is better than BAS and PSO. The algorithm was applied to the sample measurement of flatness error, the tolerance value of flatness is 0.00615mm, the average tolerances of BAS-PSO are reduced 0.0023mm, 0.00127mm, 0.00058mm, and 0.0037mm compering with the least square method (LSM), genetic algorithm (GA), BAS, and PSO, which verified the feasibility and superiority of the algorithm.
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2021, Vol. 42 
