用有限元法和人工神经网络估计金刚石激光加工参数

V. Emelyanov, E. B. Shershnev, Y. Nikitjuk, S. I. Sokolov, I. Y. Aushev
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引用次数: 0

摘要

本文采用人工神经网络与有限元法相结合的方法对激光加工金刚石过程进行了仿真。在ANSYS中生成了训练数据阵列和测试数据阵列。对600种输入参数进行了计算,其中60种用于测试人工神经网络。研究了神经网络模型参数对激光加工区域温度确定精度的影响。建立的神经网络参数在预测钻石激光辐射产生的温度方面提供了可接受的结果。所得结果可用于金刚石激光加工工艺参数的确定。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Estimating the Parameters of Laser Processing of Diamonds Using the Finite Element Method and Artificial Neural Networks
This paper provides the simulation of laser processing of diamonds by using a combination of artificial neural networks and the finite element method. The training data array and the data array for testing neural networks were generated in ANSYS. The calculations were performed for 600 types of input parameters, 60 of which were used to test artificial neural networks. The influence of the parameters of neural network models on the accuracy of determining temperatures in the laser processing area were studied. The parameters of neural networks were established that provide acceptable results in predicting temperatures generated by laser radiation in diamonds. The results obtained can be used to determine the technological parameters of the laser processing of diamonds.
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