Optimization of the Welding Parameters of High-Quality Aluminum/Copper FSSW Joints Using Taguchi Method Combined with Back Propagation Neural Network and Genetic Algorithm

IF 1.8 4区 材料科学 Q2 MATERIALS SCIENCE, CHARACTERIZATION & TESTING
S. Ahmadpour Kasgari, M. R. M. Aliha, F. Berto
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Abstract

Due to the different superior properties of lightweight and high-strength aluminum and high-conductivity copper metals, the joining of the two is very common and important in today’s industrial applications. Generally, there is no formula to follow for the setting of welding parameters, and the setting is completely based on the past knowledge and experience of experts. Once the range of expert experience is exceeded, the optimal parameters cannot be effectively set, which may easily lead to poor welding quality. This research aims to develop an economical and effective Taguchi experimental design method for achieving the highest shear strength value for aluminum/copper friction stir spot welded joints. Three independent welding process variables were considered including the pin rotation speed, dwell time, and downward pressure. Different optimization techniques such as Taguchi, TOPSIS, artificial neural network, genetic algorithm, and their combinations were utilized for obtaining the best ranges of input welding parameters to achieve the maximum shear strength values. The optimal combination of process parameters was found at the rotation speed of 1800 r/min, the dwell time of 15 s, and the downward pressure of 0.2 mm. The results showed that the integration of the TOPSIS method, neural network, and genetic algorithm provides the best combination of parameter values for the verification of shear strength experiments. According to the performed analyses, the degree of influence of the independent variables on the shear strength of bi-material joints can be ranked as: dwell time > pin rotation speed > downward pressure.

Abstract Image

使用田口方法结合反向传播神经网络和遗传算法优化高质量铝/铜快速焊接接头的焊接参数
摘要由于轻质高强度铝和高导电率铜金属具有不同的优越性能,二者的连接在当今的工业应用中非常普遍和重要。一般来说,焊接参数的设定没有公式可循,完全是根据专家以往的知识和经验设定的。一旦超出专家经验的范围,就无法有效设定最佳参数,从而容易导致焊接质量低下。本研究旨在开发一种经济有效的田口实验设计方法,以实现铝/铜搅拌摩擦点焊接头的最高剪切强度值。研究考虑了三个独立的焊接工艺变量,包括销钉旋转速度、停留时间和向下压力。利用不同的优化技术,如 Taguchi、TOPSIS、人工神经网络、遗传算法及其组合,以获得最佳的输入焊接参数范围,从而达到最大的剪切强度值。在转速为 1800 r/min、停留时间为 15 s、下压力为 0.2 mm 的条件下,找到了工艺参数的最佳组合。结果表明,TOPSIS 法、神经网络和遗传算法的整合为剪切强度实验验证提供了最佳的参数值组合。根据分析结果,自变量对双材料接头剪切强度的影响程度可排序为:停留时间>;销轴旋转速度>;向下压力。
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来源期刊
Physical Mesomechanics
Physical Mesomechanics Materials Science-General Materials Science
CiteScore
3.50
自引率
18.80%
发文量
48
期刊介绍: The journal provides an international medium for the publication of theoretical and experimental studies and reviews related in the physical mesomechanics and also solid-state physics, mechanics, materials science, geodynamics, non-destructive testing and in a large number of other fields where the physical mesomechanics may be used extensively. Papers dealing with the processing, characterization, structure and physical properties and computational aspects of the mesomechanics of heterogeneous media, fracture mesomechanics, physical mesomechanics of materials, mesomechanics applications for geodynamics and tectonics, mesomechanics of smart materials and materials for electronics, non-destructive testing are viewed as suitable for publication.
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