Abstract :
Based on the analysis of existent evaluation methods for spatial straightness 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 spatial straightness 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 high. Then, the objective function calculation approaches for using the ACO to evaluate minimum zone error are formulated. Finally, the control experiment results evaluated by different optimal methods such as the least square, simplex search, Powell search and Genetic Algorithm, indicate that the proposed method does provide better accuracy on spatial straightness error evaluation, and it has fast convergent speed as well as using computer and popularizing application easily.
Keywords :
error analysis; genetic algorithms; Powell method; ant colony algorithm; genetic algorithm; minimum zone error; spatial straightness error evaluation; Ant colony optimization; Chebyshev approximation; Computer errors; Coordinate measuring machines; Error correction; Genetic algorithms; ISO standards; Least squares approximation; Least squares methods; Linear programming;
