Year of Publication

2008

Degree Name

Doctor of Philosophy (PhD)

Document Type

Dissertation

College

Engineering

Department

Electrical Engineering

First Advisor

Dr. YuMing Zhang

Abstract

GMAW (Gas Metal Arc Welding) is one of the most important arc welding processes being adopted in modern manufacturing industry due to its advantages in productivity, energy efficiency and automation. By monitoring and improving some of the important properties of GMAW such as production rate, metal transfer and base metal heat input, researchers could bring the process efficiency and stability to a new level. In recent years, some innovative modifications of GMAW such as Twins, Tandem and laser-MIG hybrid welding have been adopted into many industrial applications for better productivity.

In this dissertation, a novel GMAW called DB-GMAW (Dual Bypass Gas Metal Arc Welding) using two GTAW torches and one GMAW torch to construct a welding system, is proposed and developed. In DB-GMAW, two GTAW torches perform the bypass system which decouples the total welding current into base metal current and bypass current after the melt down of filler wire. Compared to conventional GMAW, DB-GMAW has many advantages in droplet formation, base metal heat input and penetration achievement due to its unique characteristics in welding arc and current flow. In the first place of the research, experimental system of DB-GMAW is constructed. Then, sufficient experiments under different parameters are performed to provide us a good understanding of the behaviors and characteristics of this novel GMAW process. Observation about metal transfer formation and base metal heat input is studied to verify its theoretical analysis. Full penetration of work piece via DB-GMAW is achieved based on a series of parameter testing experiments. Moreover, image processing techniques are applied to DB-GMAW to monitor the welding process and construct a feedback system for control.

Considering the importance of maintaining stable full penetration during many welding applications, a nonlinear model of DB-GMAW full penetration is developed in this dissertation. To do that, we use machine vision techniques to monitor the welding profile of the work piece. A control algorithm based on the nonlinear model using adaptive control technique is also designed. The achievement of this dissertation provides a fundamental knowledge of a novel welding process: DB-GMAW, and a good guidance for further studies about DBGMAW.

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