Wavelet packet transformation-based improved acoustic emission method for structural damage identification

Abstract Acoustic emission (AE) technique has emerged as a sophisticated nondestructive testing technique that plays a crucial role in detecting and localizing damage in structures. This paper proposes a damage visualization approach by leveraging the classical signal decomposition capabilities of Wavelet Packet Transformation (WPT) and the classification abilities of the Gaussian Mixture Model (GMM). First, WPT decomposes AE signals acquired from the instrumented structure at different loading stages. The coordinates (e.g. x and y ) of AE events identified by the localization model using denoised AE components obtained from WPT are then determined. The extracted coordinates are used in the GMM model to visualize the location of the damage during the intermediate and final loading stages. The proposed method is validated using a suite of lab-scale experimental studies of concrete beams. The study compares the outcomes of the proposed method with those obtained from a traditional digital image correlation (DIC) system for both intermediate and final stages of damage. The results indicate that the proposed framework effectively visualizes the locations of various types of damage, such as flexural and shear cracks, at an early stage compared to the DIC. This demonstrates the proposed method’s capability to be a reliable tool for early damage localization and visualization in concrete structures.