Neural network modeling for dynamic pulsed GTAW process with wire filler based on MATLAB |
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Authors: | Zhao Dongbin Chen Shanben Wu Lin Chen Qiang |
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Affiliation: | 1. Department of Mechanical Engineering,Tsinghua University,Beijing,100084 2. Welding Department,Shanghai Jiaotong University,Shanghai,200030 3. National Key Laboratory of Advanced Welding Production Technology,Harbin Institue of Technology,Harbin,150001 |
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Abstract: | Double-sided weld pool shapes were determined by multiple welding parameters and wire feed parameters during pulsed GTAW with wire filler. Aiming at such a system with multiple inputs and outputs, an effective modeling method, consisting of the impulse signal design, model structure and parameter identification and verification, was developed based on MATLAB software. Then, dynamic neural network models, TDNNM (Topside dynamic neural network model) and BHDNNM (Backside width and topside height dynamic neural network model), were established to predict double-sided shape parameters of the weld pool. The characteristic relationship of the welding process was simulated and analyzed with the models. |
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Keywords: | GTAW with wire filler dynamic process modeling neural network MATLAB |
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