Vibration signal denoising for structural health monitoring by residual convolutional neural networks

Vibration signal denoising for structural health monitoring by residual convolutional neural networks

In vibration based structural health monitoring (SHM), measurement noise inevitably exists in the vibration data, which significantly influences the usability and quality of measured vibration signals for structural identification and condition monitoring. As a result, there is a high demand for dev...

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Bibliographic Details
Main Authors: Fan, G., Li, Jun, Hao, Hong
Format: Journal Article
Language:English
Published: ELSEVIER SCI LTD 2020
Subjects:
Science & Technology
Technology
Engineering, Multidisciplinary
Instruments & Instrumentation
Engineering
Denoising
Modal identification
Noise
Residual convolutional neural network
Structural health monitoring
Vibration signal
DAMAGE IDENTIFICATION
FREQUENCY-DOMAIN
SPEECH ENHANCEMENT
FEATURE-EXTRACTION
MODAL-ANALYSIS
WAVELET
SUBSTRUCTURE
Online Access:http://purl.org/au-research/grants/arc/FL180100196
http://hdl.handle.net/20.500.11937/91514

Internet

http://purl.org/au-research/grants/arc/FL180100196
http://hdl.handle.net/20.500.11937/91514

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