中国激光, 2010, 37 (7): 1856, 网络出版: 2010-07-13
基于径向基函数神经网络的激光焊接熔池光强分布预测
Prediction on Light Intensity Distribution of Laser Welding Melt Pool Based on Radial Basis Function Neural Network
激光技术 光强分布预测 径向基函数神经网络 非参数统计模型 laser technique light intensity distribution prediction radial basis function neural network non parametric statistical model
摘要
激光焊接过程复杂,影响因素众多,许多参数难以量化。基于归一化的径向基函数神经网络,采用非参数统计方法,建立了激光焊接熔池在时间和空间上的光强分布模型。该神经网络采用高斯函数作为径向基函数。提出了定量评价该模型预测光强分布质量的方法,并根据该评价方法,对影响光强分布模型的重要参数进行优化选择。根据优化选择结果,对两幅光强分布图形进行预测。通过预测图像与实测图像的对比证明,该神经网络可有效预测激光焊接熔池的光强分布。
Abstract
Laser welding is a complicated process,and quantitative analysis of this process is quite difficult. A non parametric statistical method of light intensity distribution modeling,based on normalized radial basis function neural network,is proposed to predict the spatiotemporal dynamics of surface optical activity in the laser welding process. This neural network adopts Gaussian function as radial basis function. A quantitative evaluation method for light intensity distribution of modeling quality is proposed. Parameters are optimized according to this evaluation method. Comparison of predicted images and testing images exhibits a good resemblance.
张健, 杨锐. 基于径向基函数神经网络的激光焊接熔池光强分布预测[J]. 中国激光, 2010, 37(7): 1856. Zhang Jian, Yang Rui. Prediction on Light Intensity Distribution of Laser Welding Melt Pool Based on Radial Basis Function Neural Network[J]. Chinese Journal of Lasers, 2010, 37(7): 1856.