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Numerical Control Interpolation Algorithm of Aspheric Surface Based on the Genetic Algorithms and Neural Network

机译:基于遗传算法和神经网络的非球面数控插补算法

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When the Neural Network model is used to interpolate the non-circular curves, there are shortcomings of converging slowly and getting into the local optimum easily. A novel numerical control interpolation algorithm based on the GA (Genetic Algorithms) and NN (Neural Network) was introduced for the ultra-precision machining of aspheric surfaces. The algorithm integrated the global searching of GA with the parallel processing of NN, enhanceed the convergence speed and found the global optimum. At the end, the quintic non-circular curve was taken as an example to do the emulation and experiment. The results prove that this algorithm can fit the non-circular curve accurately, improve the precision of numerical control interpolation and reduce the number of calculating and interpolation cycles.
机译:当使用神经网络模型对非圆曲线进行插值时,存在收敛缓慢且容易陷入局部最优的缺点。提出了一种基于遗传算法和神经网络的数控插补算法,用于非球面的超精密加工。该算法将遗传算法的全局搜索与神经网络的并行处理相结合,提高了收敛速度,并找到了全局最优解。最后以五阶非圆曲线为例进行仿真和实验。结果证明,该算法能准确拟合非圆曲线,提高了数控插补的精度,减少了计算和插补周期。

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