Deep learning|based indirect bridge damage identification system

Deep learning-based indirect bridge damage identification system

This study employs a powerful class of deep learning algorithm to develop a damage identification system using measurements on an instrumented travelling train.

Bridge damage identification using deep learning-based ...

Convolutional Neural Networks (CNNs) are the most used deep neural networks using imagery in the SHM community. Another indirect approach is to transform ...

Evaluation of bridge structure damage based on deep learning ...

Deep learning-based indirect bridge damage identification system. Struct Health Monit. 2023; 22(2): 897-912. Google Scholar. [3]. Salet TAM ...

Deep-Learning-Based Drive-by Damage Detection System for ...

The fundamental principle in an indirect vibration-based damage identification system is to extract bridge damage signatures from on-board ...

Deep learning-based bridge damage cause estimation from multiple ...

Cha, Choi, and Büyüköztürk (Citation2017) proposed a crack detection method from images using convolutional neural networks (CNNs), a type of deep learning ...

Indirect damage detection for bridges using sensing and temporarily ...

Results showed that the decrease of bridge frequencies due to damage could be amplified by introducing the extra parked vehicle. Based on this ...

Deep learning based indirect monitoring to identify bridge natural ...

PDF | In this paper a supervised deep learning based approach to extract bridge natural frequencies from acceleration sensors on a passing train is.

The application of deep learning in bridge health monitoring

This paper focuses on the review of the recent application of DL in SHM, particularly damage detection, and provides readers with an overall understanding of ...

Deep-Learning-Based Drive-by Damage Detection System for ...

... bridge damage. The fundamental principle in an indirect vibration-based damage identification system is to extract bridge damage signatures from on-board ...

Structural damage detection using deep learning and FE model ...

Vibration-based structural health monitoring systems, on the other hand, can continuously monitor the behavior and response of structures using ...

Damage Identification Based on the Loaded Frequency Changes ...

Damage Identification Based on the Loaded. Frequency Changes and Deep Learning for Bridge. To cite this article: Yangyang Ren and Yi Ye 2021 J. Phys.: Conf ...

A deep‐learning framework for classifying the type, location, and ...

Deep-learning-based drive-by damage detection system for railway bridges. ... Deep learning-based indirect bridge damage identification system.

Machine-learning-based bridge damage detection using train-borne ...

The fundamental principle in indirect damage identification techniques is that damage causes changes in the physical properties of the structure ...

A deep‐learning framework for classifying the type, location, and ...

Deep learning‐based indirect bridge damage identification system. Structural Health Monitoring, 21(5), 2190–2205. Google Scholar. [18]. Hearn ...

Surface Damage Detection and Localization for Bridge Visual ...

Currently, computer vision and deep learning-based surface damage detection methods can achieve classification and localization of damages at ...

A Machine Learning Approach to Bridge-Damage Detection Using ...

There are several indirect methods for bridge condition monitoring that do not explicitly estimate bridge modal properties. O'Brien et al. [12] ...

Multiclass Damage Identification in a Full-Scale Bridge Using ...

“A review of vibration-based damage detection in civil engineering structures: From traditional methods to machine learning and deep learning ...

Damage identification for bridges using machine learning - arXiv

By combining FEM with sensor-based data from the KW51 bridge, the proposed damage detection strategy is used to identify damage on the arch of ...

Bridge damage identification using deep learning-based ... - engrXiv

Convolutional Neural Networks (CNNs) are the most used deep neural networks using imagery in the SHM community. Another indirect approach is to transform ...

A deep‐learning framework for classifying the type, location, and ...

1–6). https://doi.org/10.1109/ESARS-ITEC.2016.7841398; Hajializadeh D., Deep learning‐based indirect bridge damage identification system, Structural Health ...