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An acoustic emission activity detection method based on short-term waveform features: application to metallic components under uniaxial tensile test

Author
Piñal , J.F.; Delgado Prieto, M.; Romeral, L.
Type of activity
Journal article
Journal
Mechanical systems and signal processing
Date of publication
2020-08-01
Volume
142
Number
106753
First page
106753:1
Last page
106753:22
DOI
10.1016/j.ymssp.2020.106753
Project funding
Fault Tolerant Powertrain based on multiphase PMa_SynRM driven by a SiC inverter for a reliable Electric Vehicle operation
Repository
http://hdl.handle.net/2117/179899 Open in new window
URL
https://www.sciencedirect.com/science/article/pii/S0888327020301394 Open in new window
Abstract
The Acoustic Emission (AE) phenomenon has been used as a powerful tool with the purpose to either detect, locate or assess damage for a wide range of applications. Derived from its monitoring, one major current challenge on the analysis of the acquired signal is the proper identification and separation of each AE event. Current advanced methods for detecting events are primarily focused on identifying with high accuracy the beginning of the AE wave; however, the detection of the conclusion has b...
Citation
Piñal , J.F.; Delgado Prieto, M.; Romeral, L. An acoustic emission activity detection method based on short-term waveform features: application to metallic components under uniaxial tensile test. "Mechanical systems and signal processing", 1 Agost 2020, vol. 142, núm. 106753, p. 106753:1-106753:22.
Keywords
Acoustic emission, Detection algorithms, Endpoint detection, Onset detection, Performance analysis, Short-time analysis
Group of research
MCIA - Motion Control and Industrial Applications Research Group
PERC-UPC - Power Electronics Research Centre