A framework for the damage evaluation of acoustic emission signals through Hilbert-Huang transform

摘要: Abstract The acoustic emission (AE) is a powerful and potential nondestructive testing method for structural monitoring in civil engineering. Here, we show how systematic investigation of crack phenomena based on AE data can be significantly improved by the use advanced signal processing techniques. Such are fundamental source information that used as basis evaluating status material, thereby paving way new frontier innovation made data-enabled analytics. In this article, propose framework Hilbert–Huang Transform evaluation material damages (i) facilitates employment both established promising analysis criteria, (ii) provides unsupervised tools to achieve an accurate classification fracture type, discrimination between longitudinal (P-) traversal (S-) waves related event. experimental validation shows results reliable assessment health through infrastructures.