A Time–Frequency-Based Data-Driven Approach for Structural Damage Identification and Its Application to a Cable-Stayed Bridge Specimen

Structural damage identification based on structural health monitoring (SHM) data and machine learning (ML) is currently a rapidly developing research area in structural engineering. Traditional machine learning techniques rely heavily on feature extraction, where weak feature extraction can lead to...

Full description

Saved in:

Bibliographic Details
Main Authors:	Naiwei Lu, Yiru Liu, Jian Cui, Xiangyuan Xiao, Yuan Luo, Mohammad Noori
Format:	Article
Language:	English
Published:	MDPI AG 2024-12-01
Series:	Sensors
Subjects:	structural damage identification structural health monitoring convolutional neural network gram angle difference field cable-stayed bridge
Online Access:	https://www.mdpi.com/1424-8220/24/24/8007
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!

A Time–Frequency-Based Data-Driven Approach for Structural Damage Identification and Its Application to a Cable-Stayed Bridge Specimen

Similar Items