Abstract
Based on the analysis of existent evaluation methods for coaxiality errors, an intelligent evaluation method is provided in this paper. The evolutional optimum model and the calculation process are introduced in detail. According to characteristics of coaxiality error evaluation, ant colony optimization (ACO) algorithm is proposed to evaluate the minimum zone error. Compared with conventional optimum evaluation methods such as simplex search and Powell method, it can find the global optimal solution, and the precision of calculating result is very good. Then, the objective function calculation approaches for using the ACO algorithm to evaluate minimum zone error are formulated. Finally, the control experiment results evaluated by different method such as the least square, simplex search, Powell optimum methods and GA, indicate that the proposed method does provide better accuracy on coaxiality error evaluation, and it has fast convergent speed as well as using computer expediently and popularizing application easily.
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Zhang, K. (2007). Research on Coaxiality Errors Evaluation Based on Ant Colony Optimization Algorithm. In: Li, K., Fei, M., Irwin, G.W., Ma, S. (eds) Bio-Inspired Computational Intelligence and Applications. LSMS 2007. Lecture Notes in Computer Science, vol 4688. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74769-7_30
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DOI: https://doi.org/10.1007/978-3-540-74769-7_30
Publisher Name: Springer, Berlin, Heidelberg
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