Real-Time Prediction of Welding Penetration Mode and Depth Based on Visual Characteristics of Weld Pool in GMAW Process

Rongwei Yu,Zhuang Zhao,Lianfa Bai,Jing Han

doi:10.1109/access.2020.2990902

Abstract

The penetration depth of welding seam can reflect welding quality fundamentally, during the gas metal arc welding (GMAW) process, the penetration depth of welding seam fluctuates over time. At present, it lacks of reliable sensing method to predict penetration depth fluctuation accurately in real time. To solve the above problem, in this paper, proposing a real-time prediction method for weld penetration mode and depth based on two-dimensional visual characteristics of weld pool, establishing a monocular vision sensing system, extracting the area, length and width of weld pool as key two-dimensional visual characteristics. Taking the extracted current frame characteristics of weld pool as the input, the weld penetration of welding seam corresponding to current frame as the output, based on support vector machine (SVM) and back propagation (BP) neural network respectively, the real-time prediction models for weld penetration mode and depth were established. The predicted results show that the established models can accurately predict the penetration mode and penetration depth of welding seam in real time.

Highlights

In the whole welding process, the penetration depth that the soldering seam can reach is an important parameter concerned by scholars, real-time prediction and control of the weld penetration depth accurately have always been a research hotspot in the welding field [1]–[3]
Chen et al [6] proposed a method to predict the penetration mode of gas tungsten arc welding (GTAW) process based on data-driven approach, used computer vision method to extract the key features of the molten pool surface, conducted experiments under various welding conditions to establish the database, used two supervised machine learning methods such as linear regression to test the database, the importance of the surface characteristics of molten pool was analyzed
ESTABLISHMENT OF PENETRATION MODE PREDICTION MODEL FOR gas metal arc welding (GMAW) WELDING PROCESS Conducting the welding experiment by using the data in Table 1, the length of each welding seam was set to 8 cm, the experimental results are shown in Figures 7, 8 and 9, at the bottom, it is weld pool images corresponding to different positions of welding seam

Summary

Introduction

In the whole welding process, the penetration depth that the soldering seam can reach is an important parameter concerned by scholars, real-time prediction and control of the weld penetration depth accurately have always been a research hotspot in the welding field [1]–[3]. FPGA sent out a signal to trigger the color CCD acquire weld pool image, the frequency of signal is 1000 Hz, we extracted the area, length and width of the weld pool as the key characteristic parameters, provided training and test data for weld penetration mode prediction model.

Results

Conclusion