REAL-TIME IMAGE PATTERN SENSOR FOR WELD POOL PENETRATION THROUGH REFLECTION IN GTAW

In gas tungsten arc welding (GTAW), weld pool surface contains crucial information for welding development. In this research, simulate skilled welders to control the welding process and determine the penetration stages based on the weld pool reaction. This study focuses on solving the uncertainty of the liquid weld pool in joint bases. The weld pool penetration process is highly depending on how the weld pool surface shape. To observe the weld pool, reflect the weld pool surface by the laser and image on the shield glass. The experiments show that the penetration can’t be determine by the reflecting grayness due to the variability of base metal. To control the joint bases diversity, fed a tip of the wire after the arc is established. Crate the new pattern of the weld pool penetration. Experiments verified the feasibility of this method

REAL-TIME SENSING AND CONTROL OF DEVELOPING WELD PENETRATION THROUGH REFLECTION VIBRATION IN GTAW

GTAW (Gas Tungsten Arc Welding) weld pool surface is believed to contain sufficient information to determine the weld penetration, from which skilled welders are able to control the welding process to desired penetration states. However, it is unclear how human welders extract the weld penetration from the observed weld pool surface. In this research, a novel method is studied to determine the weld penetration based on the dynamic change of the weld pool surface. This study observes/measures/analyzes the development of a weld pool from partial to full penetration and correlates such change to the weld penetration. Similar trends in the weld pool surface are observed when the weld penetration changes from partial to full penetration despite the amperage used and material welded. Correlating the weld pool surface reflecting grayness and the development of the weld penetration from experiments shows: (1) the weld pool reflection intensity will increase while the weld penetration is increasing; (2) the increasing trends of weld pool reflection intensity will decrease when the full penetration is achieved; (3) the weld pool reflection intensity will increase after the full penetration is achieved. Such trend in the weld pool surface reflection intensity when the weld penetration develops is used as feedback signal to detect the weld pool penetration. To control the weld pool penetration, a first-order dynamic model is identified. Model Predictive Control (MPC) is used to control the weld penetration. Experiments verified the feasibility of this proposed method and established system