Abstract
AbstractAdditive manufacturing has the characteristics of gradual accumulation of materials in the manufacturing process. It is often superimposed layer by layer in the process of material physical shape change, which may be accompanied by hot melting, liquid material solidification, particle sintering and other processes. Due to the influence of physical environment, machine state, manufacturing principle and other factors in the whole process, performance defects of parts may occur. The traditional monitoring methods such as vision, optics and CT tomography have limitations, or can only observe the defects on the outer surface, or it is difficult to find the defects in time in the processing process, or the micro defect identification accuracy is not enough. A series of research on acoustic emission detection technology, due to the high sensitivity to high-frequency signals, can observe various phenomena of the machine itself in the processing procedure, and monitor the spatial micro faults of the whole part in the process of parts made of additive materials.KeywordsAdditive Manufacturing (AM)Acoustic Emission (AE)Condition monitoringMachine learning
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