Roundness Error Evaluation of Minimum Zone Method Based on Improved Bat Algorithm
Roundness is one of the core indexes for the evaluation of geometric accuracy of shaft-type me-chanical products,which directly affects the performance and life of the products,and accurate,fast and standardised roundness error assessment of parts has always been a hotspot of research in the field of me-trology.Therefore,this paper proposes a roundness error evaluation method based on the improved bat algo-rithm with minimum region method,which makes use of the bat algorithm's population optimisation ability,combines with the minimum region method to quickly find the optimisation of the target circle center in the roundness error model,and then calculates and solves the roundness error value.The improved bat algo-rithm increases the chaotic inertia weights and adaptive parameters to avoid the algorithm from falling into local optimality in the roundness error assessment and improve the accuracy and stability of the assessment.Through the experimental verification and analysis and comparison of the measured data,the results show that the proposed method is significantly better than the genetic algorithm in circularity error assessment,and the assessment accuracy and stability are greatly improved compared with that of the least squares method,which verifies the feasibility of the method in the application of the minimum region method for circularity error assessment.
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