Real-Time Weld Gap Monitoring and Quality Control Algorithm during Weaving Flux-Cored Arc Welding Using Deep Learning

Abstract

In the flux-cored arc welding process, which is most widely used in shipbuilding, a constant external weld bead shape is an important factor in determining proper weld quality; however, the size of the weld gap is generally not constant, owing to errors generated during the shell forming process; moreover, a constant external bead shape for the welding joint is difficult to obtain when the weld gap changes. Therefore, this paper presents a method for monitoring the weld gap and controlling the weld deposition rate based on a deep neural network (DNN) for the automation of the hull block welding process. Welding experiments were performed with a welding robot synchronized with the welding machine, and the welding quality was classified according to the experimental results. Welding current and voltage signals, as the robot passed through the weld seam, were measured using a trigger device and analyzed in the time domain and frequency domain, respectively. From the analyzed data, 24 feature variables were extracted and used as input for the proposed DNN model. Consequently, the offline and online performance verification results for new experimental data using the proposed DNN model were 93% and 85%, respectively.

The On-Line Identification and Location of Welding Interference Based on CEEMD

“…Jin developed a method using a Deep Neural Network (DNN) to monitor the weld gap and control the weld deposition rate, thereby automating the hull block welding process. The average accuracy for off-line and on-line cases was 93.7% and 87.7%, respectively [7]. An innovative approach proposed by Huang et al involves the analysis of spectral data obtained during the welding process of aluminum alloys to diagnose and detect porosity defects.…”

A Study on the Microstructure and Mechanical Properties of the Coarse Grain Heat Affected Zone in EH40 Grade High Strength Structural Steels

“…With the increasing demand for ultra-thick steel plates, research on welding technology for ultra-thick materials is being actively conducted. Conventionally, FCAW and submerged arc welding (SAW) have been widely employed for fabricating vessels because they offer advantages such as automation and wide applicability [11][12][13][14] . However, these welding methods entail degradation of productivity when applied to thick plate welding because of the large number of welding deposits 15) .…”