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首页> 美国卫生研究院文献>Materials >Quantitative Relationship Analysis of Mechanical Properties with Mg Content and Heat Treatment Parameters in Al–7Si Alloys Using Artificial Neural Network
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Quantitative Relationship Analysis of Mechanical Properties with Mg Content and Heat Treatment Parameters in Al–7Si Alloys Using Artificial Neural Network

机译：基于人工神经网络的Al-7Si合金力学性能与Mg含量和热处理参数的定量关系分析

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摘要

In this paper, an artificial neural network (ANN) model with high accuracy and good generalization ability was developed to predict and optimize the mechanical properties of Al–7Si alloys. The quantitative correlation formulas of the mechanical properties with Mg content and heat treatment parameters were established based on the transfer function and weight values. The relative importance of the input variables, Mg content and heat treatment parameters, on the mechanical properties of Al–7Si alloys were identified through sensitivity analysis. The results indicated that the mechanical properties of Al–7Si alloys were sensitive to Mg content and aging temperature. Then the individual and the combined influences of these input variables on the properties of Al–7Si alloys were simulated and the process parameters were optimized using the artificial neural network model. Finally, the proposed model was validated to be a robust tool in predicting the mechanical properties of the Al–7Si alloy by conducting experiments.
机译：在本文中，开发了一种具有高精度和良好泛化能力的人工神经网络（ANN）模型，以预测和优化Al-7Si合金的力学性能。根据传递函数和重量值，建立了力学性能与镁含量和热处理参数的定量相关公式。通过敏感性分析确定了输入变量，Mg含量和热处理参数对Al-7Si合金力学性能的相对重要性。结果表明，Al-7Si合金的力学性能对Mg含量和时效温度敏感。然后，模拟这些输入变量对Al-7Si合金性能的个体和综合影响，并使用人工神经网络模型优化工艺参数。最后，通过进行实验验证了所提出的模型是预测Al-7Si合金力学性能的可靠工具。

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