Localizing damage on stainless steel structures using acoustic emission signals and weighted ensemble regression-based convolutional neural network

• Published in: Measurement : journal of the International Measurement Confederation Vol. 211; no. C; p. 112659
• Main Authors: Ai, Li, Bayat, Mahmoud, Ziehl, Paul
• Format: Journal Article
• Language: English
• Published: United Kingdom Elsevier Ltd 01.04.2023; Elsevier
• Subjects: Acoustic emission; Convolutional neural network; Source localization; Spent fuel storage canister; Spent fuel storage canister; Acoustic emission; Source localization; Convolutional neural network

•A data fusion method is presented, which integrates AE waveform, FFT spectrum, and spectral entropy.•A weighted ensemble regression-based CNN was proposed to estimate the coordinates of damage.•Fusion data, CWT, and STFT coefficients were used as input data.•The proposed model estimates the coordin...