人工神经网络法与多元回归法模拟Ti-6al-4v板材激光切割热影响区(Haz)的比较研究

E. Mahmood
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引用次数: 0

摘要

本文研究了厚度、透镜焦距、光束功率、切割速度和气体压力等激光切割参数对热影响区宽度的影响。利用人工神经网络(ANN)和多元回归建模方法建立了两个预测模型。基于神经网络(ANN)神经元权值和方差分析(ANOVA)方法确定了激光切割参数对HAZ宽度的相对重要性。实验数据与预测数据的比较表明,(ANN)模型对HAZ的预测精度高于多元回归模型,决定系数(R2)=85.02%。
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A Comparison Study Between Modeling The Heat Affected Zone (Haz) For The Laser Cutting Of Ti-6al-4v Sheets By Using The Artificial Neural Network Method And Multi Regression Method
This research presents an attempt to study the influence of laser cutting parameters such as thickness, Lens Focal Length, Beam Power, Cutting Speed and Gas Pressure on the Heat Affected Zone (HAZ) width. Two predictive models were developed using Artificial Neural Network (ANN) and multi regression modeling method. The relative importance of laser cutting parameters on (HAZ) width was determined based on (ANN) neuron weights and (ANOVA) method. The comparison between the experimental data and the predicted data indicats that the (ANN) model has attain an accuracy for predicting (HAZ) more than the multi regression model with a coefficient of determination of (R2)=85.02%.
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