Segueix
Ignacio Gonzalez
Ignacio Gonzalez
PhD
Correu electrònic verificat a kth.se
Títol
Citada per
Citada per
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Structural health monitoring of bridges: a model-free ANN-based approach to damage detection
AC Neves, I Gonzalez, J Leander, R Karoumi
Journal of Civil Structural Health Monitoring 7, 689-702, 2017
2152017
The application of a damage detection method using Artificial Neural Network and train-induced vibrations on a simplified railway bridge model
J Shu, Z Zhang, I Gonzalez, R Karoumi
Engineering structures 52, 408-421, 2013
1262013
BWIM aided damage detection in bridges using machine learning
I Gonzalez, R Karoumi
Journal of Civil Structural Health Monitoring 5, 715-725, 2015
902015
Seasonal effects on the stiffness properties of a ballasted railway bridge
I Gonzales, M Ülker-Kaustell, R Karoumi
Engineering structures 57, 63-72, 2013
792013
A new approach to damage detection in bridges using machine learning
AC Neves, I González, J Leander, R Karoumi
Experimental Vibration Analysis for Civil Structures: Testing, Sensing …, 2018
532018
An approach to decision‐making analysis for implementation of structural health monitoring in bridges
AC Neves, J Leander, I González, R Karoumi
Structural Control and Health Monitoring 26 (6), e2352, 2019
452019
Damage detection in railway bridges using machine learning: application to a historic structure
EK Chalouhi, I Gonzalez, C Gentile, R Karoumi
Procedia engineering 199, 1931-1936, 2017
392017
Analysis of the annual variations in the dynamic behavior of a ballasted railway bridge using Hilbert transform
I Gonzalez, R Karoumi
Engineering structures 60, 126-132, 2014
352014
Study and application of modern bridge monitoring techniques
I González
KTH Royal Institute of Technology, 2011
242011
Model-free damage detection of a laboratory bridge using artificial neural networks
A Ruffels, I Gonzalez, R Karoumi
Journal of Civil Structural Health Monitoring 10 (2), 183-195, 2020
232020
The influence of frequency content on the performance of artificial neural network–based damage detection systems tested on numerical and experimental bridge data
AC Neves, I González, R Karoumi, J Leander
Structural Health Monitoring 20 (3), 1331-1347, 2021
192021
Vibration-based SHM of railway bridges using machine learning: The influence of temperature on the health prediction
EK Chalouhi, I Gonzalez, C Gentile, R Karoumi
Experimental Vibration Analysis for Civil Structures: Testing, Sensing …, 2018
102018
Bayesian deep learning for vibration-based bridge damage detection
DS Ásgrímsson, I González, G Salvi, R Karoumi
Structural health monitoring based on data science techniques, 27-43, 2022
92022
Traffic monitoring using a structural health monitoring system
IJG Silva, R Karoumi
Proceedings of the Institution of Civil Engineers-Bridge Engineering 168 (1 …, 2015
92015
Development and validation of a data-based SHM method for railway bridges
AC Neves, I González, R Karoumi
Structural Health Monitoring Based on Data Science Techniques, 95-116, 2022
82022
Application of monitoring to dynamic characterization and damage detection in bridges
I Gonzalez
KTH Royal Institute of Technology, 2014
42014
A combined model-free Artificial Neural Network-based method with clustering for novelty detection: The case study of the KW51 railway bridge
AC Neves, I González Silva, R Karoumi
IABSE Conference Seoul 2020: Risk Intelligence of Infrastructures, 9 …, 2021
32021
From the desk to the field: Recent trends in deploying wireless sensor networks for monitoring civil structures
L Mottola, T Voigt, IG Silva, R Karoumi
SENSORS, 2011 IEEE, 62-65, 2011
32011
Seasonal effects on novelty detection using ANNs for SHM
AC Neves, I González, R Karoumi, J Leander
Bridge Maintenance, Safety, Management, Life-Cycle Sustainability and …, 2021
12021
Novel AI-based railway SHM, its behaviour on simulated data versus field deployment
I Gonzalez, E Khouri, C Gentile, R Karoumi
Proceedings of the 7th Asia-Pacific Workshop on Structural Health Monitoring …, 2018
12018
En aquests moments el sistema no pot dur a terme l'operació. Torneu-ho a provar més tard.
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