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Optimization of Friction Stir Welding by fuzzy logic

机译:用模糊逻辑优化搅拌摩擦焊

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摘要

Difficulty of welding with high strength and resistance to fatigue failure of the aluminum alloys, hindering the widespread use of conventional welding methods for forming such a connection in aerospace applications. These factors led to the junction fusion welding of aluminum alloys methods quite unnoticed. Therefore, the use of solid state welding Friction welding especially Friction Stir Welding (FSW) for joining aluminum alloys system has been used widely. The parameters that effect on process are gender and tool geometry, rotational speed and forward, tilt angle and vertical force noted. In present research, the effect of rotational speed and forward on mechanical properties of 2024 aluminum alloy, evaluated by experiments .in order to do this study, because of the Wide range of parameter variations on mechanical properties, we should do several expensive experimental tests. In order to decrease the amount of experimental tests, Mamdani-Type Fuzzy implication, have been chosen. In this paper, by knowing the capability of fuzzy logic in create an intelligent relationship between the input and output data, the relationship between the forward and rotational speed as an inputs and mechanical properties as an outputs based on experimental data have been proposed. The results indicated that by adopting an appropriate fuzzy method, both the number of experimental tests and mechanical properties of welded FSW, optimized.
机译:铝合金具有高强度的焊接难度和耐疲劳破坏性,阻碍了常规焊接方法在航空航天应用中广泛用于形成这种连接。这些因素导致铝合金接头的熔焊方法未引起人们的注意。因此,广泛使用固态焊接摩擦焊接,特别是摩擦搅拌焊接(FSW)来连接铝合金系统。影响工艺的参数是性别和工具的几何形状,转速和前进,倾斜角和垂直力。在本研究中,通过实验评估了转速和前进速度对2024铝合金力学性能的影响。为了进行这项研究,由于参数变化对力学性能的影响范围很广,我们应该进行一些昂贵的实验测试。为了减少实验测试的数量,选择了Mamdani型模糊蕴涵。在本文中,通过了解模糊逻辑在输入和输出数据之间建立智能关系的能力,提出了基于实验数据的正向和旋转速度作为输入以及机械性能作为输出之间的关系。结果表明,通过采用适当的模糊方法,可以优化焊接FSW的实验次数和力学性能。

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