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- Title
PATTERN RECOGNITION STUDY OF ACOUSTIC EMISSION SIGNALS OF AIRCRAFT FATIGUE CRACKING BASED ON WAVEFORM ANALYSIS AND ARTIFICIAL NEURAL NETWORKS.
- Authors
ZHEN-LONG HU; GONG-TIAN SHEN; GUAN-HUA WU; SHI-FENG LIU; ZHAN-WEN WU
- Abstract
In this paper, SOM neural network was used to identify the AE signal waveforms of aircraft fatigue test, which produced a group of suspected crack signals. Three peaks of relatively large energy appear simultaneously in frequency spectra. The frequency of peak 3 (168.5 kHz) was consistent with previous result (175.8 kHz), showing characteristics of crack AE signal.
- Subjects
ARTIFICIAL neural networks; SELF-organizing maps; ACOUSTIC emission; AIRPLANE testing; FATIGUE life
- Publication
Journal of Acoustic Emission, 2011, Vol 29, p309
- ISSN
0730-0050
- Publication type
Article