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Cited article:

Machine learning-based denoising of acoustic emission signals for fatigue crack growth monitoring in metallic piping materials

Zengchao Wu, Mengyu Chai, Zhenghui Mo, Ke Zuo and Hao Li
Measurement 282 122046 (2026)
https://doi.org/10.1016/j.measurement.2026.122046

Identification of fatigue damage evaluation using entropy of acoustic emission waveform

Farhan Tanvir, Tariq Sattar, David Mba and Graham Edwards
SN Applied Sciences 2 (1) (2020)
https://doi.org/10.1007/s42452-019-1694-7

Use of full-field measurements for understanding acoustic emission (AE) signals from 15CDV6 ESR steel specimens

Digendranath Swain, B. Binu, Yogesh, et al.
Procedia Structural Integrity 14 207 (2019)
https://doi.org/10.1016/j.prostr.2019.05.027