Bridge Damage Identification Using Deep Neural Networks on Time–Frequency Signals Representation

Bridge Damage Identification Using Deep Neural Networks on Time–Frequency Signals Representation

For the purpose of maintaining and prolonging the service life of civil constructions, structural damage must be closely monitored. Monitoring the incidence, formation, and spread of damage is crucial to ensure a structure’s ongoing performance. This research proposes a unique approach for multiclas...

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Bibliographic Details
Main Authors: Pasquale Santaniello, Paolo Russo
Format: Article
Language:English
Published: MDPI AG 2023-07-01
Series:Sensors
Subjects:
structural health monitoring
deep learning
vibrational damage detection
synchrosqueezing transformation
feature extraction
Online Access:https://www.mdpi.com/1424-8220/23/13/6152

Internet

https://www.mdpi.com/1424-8220/23/13/6152

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