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Study On Algorithm Of Dwell Time In Ion Beam Figuring Based On RBF Neural Network

机译:基于RBF神经网络的离子束成形停留时间算法研究。

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摘要

Give the figures, which describe the relation between Ion Beam Figuring parameters(Ion beam density, energy, incident angle) and removal features based on SRIM software, the beam removal function model is built and proposed an algorithm of dwell time using RBF neural network optical controlling removal function and processing route. Then, Analyzed the error of algorithm and did some related compensation researches. Results showed that under a certain accuracy, the proposed algorithm can greatly speed up, control more optimization, make the IBF technology more practical, promoting the further development of the super precision optical surface processing technology.
机译:给出数字,描述基于SRIM软件的离子束图形参数(离子束密度,能量,入射角)与去除特征之间的关系,建立离子束去除函数模型,并提出了一种使用RBF神经网络光学的停留时间算法。控制清除功能和处理路线。然后,分析了算法的误差,并进行了相关的补偿研究。结果表明,在一定的精度下,该算法可以大大提高速度,控制更多的优化,使IBF技术更加实用,促进了超精密光学表面处理技术的进一步发展。

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