Energy Characterization of Short-Circuiting Transfer of Metal Droplet in Gas Metal Arc Welding

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• 作者：Luo Yi ; Zhu Yang ; Xie Xiaojian ; Wan Rui
• 刊名：Metallurgical and Materials Transactions B
• 出版年：2015
• 出版时间：August 2015
• 年：2015
• 卷：46
• 期：4
• 页码：1924-1934
• 全文大小：3,862 KB
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• 作者单位：Luo Yi (1) (2)
  Zhu Yang (1) (2)
  Xie Xiaojian (1) (2)
  Wan Rui (1) (2)
  
  1. School of Material Science and Engineering, Chongqing University of Technology, No. 69, Hongguang Avenue, Banan District, Chongqing, 400054, P.R. China
  2. Chongqing Municipal Engineering Research Center of Institutions of Higher Education for Special Welding Materials and Technology, Chongqing, 400054, P.R. China
  
• 刊物类别：Chemistry and Materials Science
• 刊物主题：Chemistry
  Materials Science
  Manufacturing, Machines and Tools
  Metallic Materials
  Operating Procedures and Materials Treatment
  Characterization and Evaluation Materials
  Numerical and Computational Methods in Engineering
  
• 出版者：Springer Boston
• ISSN：1543-1916

文摘

The structure-borne acoustic emission (AE) signals were detected in real time in gas metal arc (GMA) welding and pulse GMA (P-GMA) welding. According to the AE signals, the mode of short-circuiting transfer was analyzed, and the energy gradient and total energy were calculated. The calculation to the AE signals of one metal droplet transfer (MDT) showed that the energy gradient increased with increasing welding heat input not only in GMA welding but also in P-GMA welding. The energy gradient of one MDT in P-GMA welding was higher than that in GMA welding, which indicated that a high energy gradient was the basic reason for the additional vibration energy provided by pulse effect in P-GMA welding. The total energy of AE signals increased with increasing welding heat input not only in GMA welding but also in P-GMA welding. The total energy of AE signals in P-GMA welding was higher than that in GMA welding, which indicated that the additional vibration energy provided by welding pulses was the main cause of the grain structure refining in P-GMA welding. So, the results provided another means to predict the weld grain size and optimize the welding process by AE signals detected in welding.