Unsupervised real‐time SHM technique based on novelty indexes-Reference-Cited by-同舟云学术

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Unsupervised real‐time SHM technique based on novelty indexes

Published:2019-05-16 Issue:7 Volume:26 Page:e2364
ISSN:1545-2255
Container-title:Structural Control and Health Monitoring
language:en
Short-container-title:Struct Control Health Monit

Author:

Almeida Cardoso Rharã¹^ORCID,Cury Alexandre²^ORCID,Barbosa Flavio²^ORCID,Gentile Carmelo³^ORCID

Affiliation:

1. Department of Civil EngineeringUniversity of Ouro Preto, Campus Universitário Ouro Preto Brazil

2. Department of Applied Computational MechanicsUniversity of Juiz de Fora, Rua José Lourenço Kelmer, Campus Universitário Juiz de Fora Brazil

3. Department of Architecture, Built environment and Construction engineering (DABC)Politecnico di Milano Milan Italy

Publisher

Wiley

Subject

Mechanics of Materials,Building and Construction,Civil and Structural Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/stc.2364

Reference44 articles.

1. Quantification and localisation of damage in beam-like structures by using artificial neural networks with experimental validation

2. Sense of Sensing: From Data to Informed Decisions for the Built Environment

3. Structural Damage Detection of Cable-Stayed Bridges Using Changes in Cable Forces and Model Updating

4. Correlation-Based Damage Detection for Complicated Truss Bridges Using Multi-Layer Genetic Algorithm

5. Structural health monitoring for flexible bridge structures using correlation and sensitivity of modal data

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1. Machine learning and cointegration for structural health monitoring of a model under environmental effects;Expert Systems with Applications;2024-03

2. A Transfer Learning Application for Damage Identification Across a Population of Experimental Bridges;Lecture Notes in Civil Engineering;2024

3. Unsupervised Learning Techniques for Vibration-Based Structural Health Monitoring Systems Driven by Data;Handbook of Research on AI and ML for Intelligent Machines and Systems;2023-11-27

4. Time-Domain Structural Damage Identification Using Ensemble Bagged Trees and Evolutionary Optimization Algorithms;Structural Control and Health Monitoring;2023-03-15

5. Novelty detection on a laboratory benchmark slender structure using an unsupervised deep learning algorithm;Latin American Journal of Solids and Structures;2023

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