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首页> 外文期刊>Chinese journal of mechanical engineering >ARTIFICIAL NEURAL NETWORK AND FUZZY LOGIC CONTROLLER FOR GTAW MODELING AND CONTROL
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ARTIFICIAL NEURAL NETWORK AND FUZZY LOGIC CONTROLLER FOR GTAW MODELING AND CONTROL

机译:用于GTAW建模和控制的人工神经网络和模糊逻辑控制器

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摘要

An artificial neural network(ANN) and a self-adjusting fuzzy logic controller(FLC) for modeling and control of gas tungsten arc welding(GTAW) process are presented. The discussion is mainly focused on the modeling and control of the weld pool depth with ANN and the intelligent control for weld seam tracking with FLC. The proposed neural network can produce highly complex nonlinear multi-variable model of the GTAW process that offers the accurate prediction of welding penetration depth. A self-adjusting fuzzy controller used for seam tracking adjusts the control parameters on-line automatically according to the tracking errors so that the torch position can be controlled accurately.
机译:提出了一种用于气体保护钨极氩弧焊(GTAW)过程建模与控制的人工神经网络(ANN)和自调节模糊逻辑控制器(FLC)。讨论主要集中在使用ANN对焊池深度进行建模和控制,以及使用FLC进行焊缝跟踪的智能控制。所提出的神经网络可以生成GTAW过程的高度复杂的非线性多变量模型,该模型可提供对焊接熔深的准确预测。用于接缝跟踪的自调节模糊控制器根据跟踪误差自动在线调节控制参数,从而可以精确地控制割炬位置。

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