Feasibility study of using acoustic signals for online monitoring of the depth of weld in the laser welding of high-strength steels

It is a trend to use high-strength steels in the automobile industry because of their good formability, weldability, and high strength–volume ratio. In order to achieve quality control, it is necessary to monitor the welding process online. In this paper, acoustic signals generated during the laser welding process of high-strength steel DP980 were recorded and analysed. A microphone was used to acquire the acoustic signals. A spectral subtraction method was used to reduce the noise in the acoustic signals, and a Welch–Bartlett power spectrum density estimation method was used to analyse the frequency characteristics of the acoustic signals. The results indicate that good welds with full penetration (FP) could be clearly distinguished from bad welds with partial penetration (PP). An algorithm based on the different sound pressures between FP and PP was developed to identify the penetration state in the time domain. Another algorithm based on the different frequency characteristics from 500 to 1500Hz between FP and PP was also developed to differentiate the penetration state. The results show that these two algorithms can effectively distinguish FP from PP. In addition, the mechanisms of the different characteristics of the acoustic signal generated from different penetration depths and modes were also analysed and discussed. This study shows that it is feasible to use acoustic signals to achieve online monitoring of the penetration states during the laser welding of high-strength steel DP980 in a noisy environment by applying proper digital signal processing methods. The acquired acoustic signal could be used as a feedback signal to control the depth of weld penetration in the laser welding process.