Feature Extraction Of Acoustic Emission Signal Of Spatter Phenomenon In The SLM Process Based On Improved GA-VMD Algorithm

Abstract

Acoustic emission(AE) signals are generated during the SLM process, which contains much information about the spatter phenomenon. In this paper, an experimental platform from of SLM process is built. It is used acquisition the AE signals of the spatter phenomenon in the SLM process to realize the feature extraction of the spatter phenomenon. A method combining the improved Genetic Algorithm(GA) with the Variational Mode Decomposition(VMD) algorithm is proposed. First, The AE signals are analyzed in the time domain, frequency- domain, and time-frequency domain. Obtain the time-frequency feature of the AE signals of the spatter phenomenon. Then, the VMD algorithm is optimized by the improved GA, and the optimal parameter combination of the VMD algorithm is obtained. Finally, the feature extraction of AE signals of spatter phenomenon by optimized VMD algorithm. The results show that the feature frequency of the AE signals of the spatter phenomenon mainly ranges from 169.448KHz.