Research on detection of welding penetration state during robotic GTAW process based on audible arc sound

Abstract

Purpose -Penetration state is one of the most important factors for judging the quality of a gas tungsten arc welding (GTAW) joint. The purpose of this paper is to identify and classify the penetration state and welding quality through the features of arc sound signal during robotic GTAW process. Design/methodology/approach -This paper tried to make a foundation work to achieve on-line monitoring of penetration state to weld pool through arc sound signal. The statistic features of arc sound under different penetration states like partial penetration, full penetration and excessive penetration were extracted and analysed, and wavelet packet analysis was used to extract frequency energy at different frequency bands. The prediction models were established by artificial neural networks based on different features combination. Findings -The experiment results demonstrated that each feature in time and frequency domain could react the penetration behaviour, arc sound in different frequency band had different performance at different penetration states and the prediction model established by 23 features in time domain and frequency domain got the best prediction effect to recognize different penetration states and welding quality through arc sound signal. Originality/value -This paper tried to make a foundation work to achieve identifying penetration state and welding quality through the features of arc sound signal during robotic GTAW process. A total of 23 features in time domain and frequency domain were extracted at different penetration states. And energy at different frequency bands was proved to be an effective factor for identifying different penetration states. Finally, a prediction model built by 23 features was proved to have the best prediction effect of welding quality.

Key Technology of Intelligentized Welding Manufacturing and Systems Based on the Internet of Things and Multi-Agent

“…In addition, theoretical research and experiments have also verified that the arc sound signal can reflect the welding penetration state [49]. This shows that the arc sound signal contains important information about weld quality [50][51][52]. The arc sound monitoring agent designed in this paper belongs to a hybrid agent of software and hardware, and uses the Internet of Things communication technology (USB communication protocol) to integrate the agent into a unified network environment.…”

Measurement and estimation of the weld bead geometry in arc welding processes: the last 50 years of development

“…Many works are oriented to detect the total or partial penetration (see Fig. 4) [1,2,12,[27][28][29][30][31][32][33][34][35][36][37][38][39][40][41] and not for obtaining a useful value for the control system algorithm.…”

“…The acoustic signal was used to detect defects in [33,94,101,[118][119][120] or to identify the transfer mode in [121]. Figure 12 shows the variation of the waveform of the acoustic signal for different penetration states.…”

“…Ultrasonic contact scans used to detect discontinuities in solidified welding metal (adapted from[112])Fig. 12Acoustic signal of the arc related to the penetration status (adapted from[33]) Weld pool oscillation frequency related to penetration: a partial penetration; b total penetration (adapted from[28])…”

Acquisition of welding skills in industrial robots

“…The authors claimed that based on the measured current, the equivalent sound can be re-created. Lv et al (2013) proposed a foundation work to achieve the identification of the penetration state and welding quality through the use of the arc sound signal features during the robotic GTAW process. A total of 23 features in time domain and frequency domain were extracted at different penetrations.…”