Real-time Measurement of Weld Pool Oscillation Frequency in GTAW-P Process-Reference-Cited by-同舟云学术

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Real-time Measurement of Weld Pool Oscillation Frequency in GTAW-P Process

Published:2017-10 Issue: Volume:29 Page:419-426
ISSN:1526-6125
Container-title:Journal of Manufacturing Processes
language:en
Short-container-title:Journal of Manufacturing Processes

Author:

Li Chunkai,Shi Yu,Du Leiming,Yufen Gu,Zhu Ming

Funder

National Natural Science Foundation of China

Outstanding Students Overseas Exchange Foundation of Lanzhou University of Technology of China

ong Liu Outstanding Talent Training Plan of Lanzhou University of Technology of China

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Management Science and Operations Research,Strategy and Management

Reference21 articles.

1. Sensing system for weld process control;Wikle;J Mater Process Technol,1999

2. Artificial neural network approach for estimating weld bead width and depth of penetration from infrared thermal image of weld pool;Ghanty;Sci Technol Weld Join,2008

3. ANFIS modeling of human welder's response to three-dimensional weld pool surface in GTAW;Liu;J Manuf Sci Eng,2013

4. Analytical reconstruction of three-dimensional weld pool surface in GTAW;Wang;J Manuf Process,2013

5. Chracterization of Three-Dimensional Weld Pool Surface in GTAW;Zhang;Weld J,2012

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1. Effect of high pulse frequency on microstructure and mechanical properties of Inconel 718 alloy prepared by wire filling stepped-dual pulsed GTA-AM;Journal of Manufacturing Processes;2024-08

2. Predictive analysis and feature extraction of weld penetration in P-GMAW based on interpretable deep learning;Journal of Manufacturing Processes;2024-08

3. Prediction of internal welding penetration based on IR thermal image supported by machine vision and ANN-model during automatic robot welding process;Journal of Advanced Joining Processes;2024-06

4. Review on the Application of the Attention Mechanism in Sensing Information Processing for Dynamic Welding Processes;Journal of Manufacturing and Materials Processing;2024-01-28

5. Penetration state recognition based on stereo vision in GMAW process by deep learning;Journal of Manufacturing Processes;2023-03

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