Fig. 6 — The MA model fitting result for the weld pool width. surface and its reflection from the specular weld pool surface is intercepted and imaged by a CCD camera (camera 1 in Fig. 3). It is known that arc light is an omnidirectional light source. Its intensity decreases quadratically with the distance traveled, but the laser, due to its coherent nature, does not significantly lose its intensity. Hence, it is possible to intercept the reflection of the illumination laser from the weld pool surface with an imaging plane placed at an appropriate distance from the arc. From the distorted reflection pattern on the imaging plane and the assumption of a smooth weld pool surface, the 3D shape of the weld pool surface can be obtained. By using specific image processing and reconstruction algorithms (Ref. 16), a 3D specular weld pool can be reconstructed in real-time (a sample reconstructed weld pool is shown in the lower right of Fig. 3). Experiment Data Stainless steel pipe was welded using the direct current electrode negative GTAW process. The pipe is stainless steel 304. The outer diameter and wall thickness of the pipe are 113.5 and 2.03 mm, respectively. Six dynamic experiments were conducted to model the correlation between the welding speed and 3D weld pool characteristic parameters. The welding speed was randomly changed from 0.5 to 1.5 mm/s. The welding current was from 40 to 50 A to ensure complete joint penetration, yet kept unchanged during each experiment. Specifically, in Experiments 1 and 5 the welding speed randomly varied from 0.8 to 1.5 mm/s. The welding current A B C D E F was set at 50 A. In Experiments 2 and 3, the welding speed varied from 0.5 to 1.2 mm/s, and the welding speed was 40 A. In Experiments 4 and 6, the welding speed varied from 0.65 to 1.35 mm/s, and the welding speed was set at 45 A. Other experimental parameters are detailed in Table 1. The sampling period in this study was 0.5 s. Figure 4 plots the system input (welding speed) and outputs (weld pool width, length, and convexity). As can be observed, the weld pool parameters are fluctuating because of the changing welding speed. Figure 5 shows the histogram of the experimental data (plotted in Fig. WELDING RESEARCH 128-s WELDING JOURNAL / APRIL 2015, VOL. 94 Fig. 7 — ARMA model errors with respect to order of previous measurement and order of input. Fig. 8 — ARMA modeling results.
Welding Journal | April 2015
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