A new method for evaluating roundness error based on improved bat algorithm

Abstract

Roundness error is one of the core indicators for evaluating the geometric accuracy of round parts mechanical products, directly affecting product performance and service life. In the field of metrology, the accurate, rapid and standardized assessment of roundness error has always been a hot topic. This paper proposed a new method for evaluating roundness error based on improved bat algorithm. This method was based on the new geometric product specification for extraction, filtering and fitting. Based on the advantages of solving optimization problems using the bat algorithm, transformed the roundness error evaluation problem using the minimum zone method into a problem of using the bat algorithm to find the center of the minimum zone circle, then further solved for the roundness error value. Also, this algorithm effectively avoided falling into local optimal solutions by introducing chaotic inertia weights during the velocity update phase, it improved the accuracy and speed of the evaluation. Introduced adaptive parameters during the loudness and emission rate update phases to enhance the algorithm’s global search capability, it enhanced the stability of the algorithm. The experimental results indicated, the efficiency of roundness error evaluation in the new method was significantly better than that of the genetic algorithm, the simplex algorithm and the emperor penguin algorithm. There was a significant improvement in evaluation accuracy and stability. The feasibility of this method in roundness error evaluation using the minimal zone method was validated.