Arc length identification based on arc acoustic signals in GTA-WAAM process

Gas tungsten arc (GTA) is a heat source commonly used in wire arc additive manufacturing (WAAM) and arc welding. During the WAAM and arc welding process, the GTA arc length has a significant influence on the quality of deposition layer and deposition conditions. Therefore, the monitoring of arc length is conducive to the automatic control of the manufacturing process. This paper studies the characteristics of arc acoustic signals with varying arc length in GTA-WAAM, and it provides a method to identify the arc length through the detection and processing of the arc acoustic signals. The signal decomposition method based on wavelet analysis is used to extract the trend signal of the variable arc acoustic signal, and the quantitative relationship between arc length and arc acoustic signal is deduced. The results show that the arc acoustic signal fluctuates regularly with the continuous change of arc length. The basic mathematical relationship between arc length and arc acoustic signal indicates the possibility of identifying the arc length. Meanwhile, the verification experimental results show that the proposed calculation method and signal processing flow are effective for arc length identification. This result provides the possibility for the application of arc acoustic signal in arc length identification and GTA-WAAM process control.