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Systems Modelling of the Internal Process Variables for Friction Stir Welding Using Genetic Multi-Objective Fuzzy Rule-Based Systems

机译:基于遗传多目标模糊规则系统的摩擦搅拌焊接内部过程变量的系统建模

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摘要

In order to design and implement a safe and practical Friction Stir Welding (FSW) process, it is crucial to understand the intricate correlations between the controllable process conditions and some internal process variables, such as tool temperature, torque and forces of tool bearing. However, because of the complexity of the FSW process, it is often difficult to derive simple and yet precise enough mathematical models to predict the correlations. In this paper, a systematic data-driven fuzzy modelling approach is developed and employed for the purpose of modelling the internal process properties of FSW, consisting of both the static and dynamic behaviours relating to welding of the AA5083 aluminium alloy. The modelling methodology includes a training data selection mechanism and a hierarchical optimisation structure, which greatly improves the modelling efficiency. The elicited models prove to be accurate and transparent, and they can be used to enhance the welding efficiency and process reliability.
机译:为了设计和实施安全实用的摩擦搅拌焊接(FSW)工艺,对于理解可控过程条件与一些内部工艺变量之间的复杂相关性是至关重要的,例如工具温度,扭矩和工具轴承的力。然而,由于FSW过程的复杂性,通常难以推导且精确的数学模型来预测相关性。在本文中,开发了一种系统数据驱动的模糊建模方法,用于建模FSW的内部工艺特性,包括与AA5083铝合金焊接有关的静态和动态行为。建模方法包括训练数据选择机制和分层优化结构,其大大提高了建模效率。引出的模型被证明是准确和透明的,它们可用于增强焊接效率和工艺可靠性。

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