Welcome to our website!
Consultation hotline: RSS EMAIL-ALERT
Evaluation of Roundness Error Based on Improved Crow Search Algorithm
CSTR:
Author:
Affiliation:

Clc Number:

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    In order to solve the problem that the conventional heuristic optimization algorithms is inefficient in evaluating roundness error and easy to fall into local optimal solution,an improved crow search algorithm was introduced to evaluate roundness error.The mathematical model for evaluating roundness errors of crow search algorithm was formulated based on the minimum zone circle(MZC) fitting criterion,and the weight coefficient was introduced to enhance the global search capability of the algorithm.At the same time,the initialization of the starting position in proximity to the center of the least squares circle was implemented to improve the algorithm′s search efficiency.Finally,the accuracy and precision of the proposed algorithm were validated through simulations and experiments.It is found that the global search ability of the improved crow search algorithm is significantly improved compared with genetic algorithm (GA),particle swarm optimization (PSO) and traditional crow search algorithm (CSA) by comparing multiple sets of data.

    Reference
    Related
    Cited by
Get Citation

张志永,郑鹏,王世强,郝用兴.基于改进乌鸦搜索算法评定圆度误差[J].机床与液压英文版,2024,52(19):65-70.

Copy
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:
  • Revised:
  • Adopted:
  • Online: October 23,2024
  • Published: October 15,2024
Article QR Code