Study On Spatter Phenomenon AE Signal Characteristics In SLM Additive Manufacturing Process

Selective Laser Melting(SLM)technique is accompanied by spatter phenomenon under the action of high-energy laser beam.The spatter phenomenon can easily lead to secondary defects such as slag inclusion,holes and cracks,and even machining failure.Therefore,the accurate detection of the spatter phenomenon is the premise to ensure the forming quality of parts.Acoustic emission(AE)is a dynamic nondestructive testing technology which takes the stress wave inside the material as the research object and has the characteristics of sensitive detection speed.Therefore,the spatter phenomenon in SLM additive manufacturing process is studied by AE technology in this paper.The spatter phenomenon AE signal is characterized by the coexistence of multiple AE sources and weak signals.It is the key to realize the AE detection of spatter phenomenon that how to separate the multi-source AE signal of spatter phenomenon,extract the feature frequency of spatter phenomenon AE signal,and provide theory and method for the online monitoring of spatter phenomenon.It has engineering application value.The main research contents and innovations of this paper are as follows:(1)An experimental platform for AE detection of spatter phenomenon in SLM additive manufacturing was established.The AE signals of background noise,spatter phenomenon under different laser power and different scanning speed were collected respectively,and the AE signals under different manufacturing conditions were analyzed in time-domain.(2)The amplitude-frequency characteristics of the background noise AE signal,the spatter phenomenon AE signal under different manufacturing conditions were analyzed.Three inherent background noise and spatter phenomenon AE signals frequency band were obtained by comparing the spectrum of the AE signal.It is concluded that the amplitude increases of the spatter phenomenon AE signal feature frequency with the increase of laser power and with the increase of scanning speed.The optimal manufacturing conditions of SLM were obtained by comparing the of molten forming quality enlarged view.(3)A method of AE multi-source signal separation based on genetic mutation particle swarm optimization-variational mode decomposition(GMPSO-VMD)algorithm was proposed.Firstly,the decomposition number and the penalty factor of parameter combination in the VMD algorithm were optimized by GMPSO algorithm.The optimal parameter combination of AE signal VMD algorithm was obtained.The effectiveness of the proposed method was verified by the GMPSO-VMD separation of simulated AE multi-source signals,and its superiority can be obtained by comparing with the empirical mode decomposition(EMD)algorithm.(4)The GMPSO-VMD algorithm was utilized to separate the background noise AE multisource signal,the spatter phenomenon AE multi-source signal under different manufacturing conditions.The experimental results show that GMPSO-VMD algorithm can accurately separate the spatter phenomenon of AE signal feature frequency,which effectively realized the spatter phenomenon of AE signal feature extraction.The optimal spatter phenomenon AE signal feature frequency band amplitude range under different manufacturing conditions was obtained by comparing the forming diagram of SLM machining parts,and the feature frequency band amplitude range was used to guide the selection of optimal manufacturing conditions for SLM additive manufacturing.