Increasing Probability of Detecting Acoustic Emission Sources Using Artificial Neural Networks

• Published in: Russian journal of nondestructive testing Vol. 58; no. 5; pp. 333 - 341
• Main Authors: Matvienko, Yu. G., Vasil’ev, I. E., Chernov, D. V., Kozhevnikov, A. V., Mishchenko, I. V.
• Format: Journal Article
• Language: English
• Published: Moscow Pleiades Publishing 01.05.2022; Springer Nature B.V
• Subjects: Acoustic emission; Acoustic Methods; Algorithms; Artificial neural networks; Broadband; Characterization and Evaluation of Materials; Chemistry and Materials Science; Emission analysis; Materials Science; Metal strips; Neural networks; Parameters; Pulse generators; Rupture tests; Strip steel; Structural Materials; Training; Transducers; artificial neural network; steel strip; probability of detecting source of acoustic signals; linear location; acoustic emission transducer; acoustic emission; pulse generator

We study the possibilities of reducing the location error of acoustic emission (AE) sources for cases where AE sources are located near AE receiving transducers (AET). Artificial neural networks (ANN) were used to reduce the location error and increase the probability of detecting such sources when...