Imperial College London
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Dr Christian Malaga-Chuquitaype

Faculty of Engineering, Department of Civil and Environmental Engineering

Senior Lecturer
 
 
 
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Contact

 

+44 (0)20 7594 5007c.malaga Website CV

 
 
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Assistant

 

Ms Ruth Bello +44 (0)20 7594 6040

 
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Location

 

322Skempton BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Gharehbaghi:2022:10.1080/24705314.2021.2018840,
author = {Gharehbaghi, VR and Kalbkhani, H and Farsangi, EN and Yang, TY and Nguyen, A and Mirjalili, S and Malaga-Chuquitaype, C},
doi = {10.1080/24705314.2021.2018840},
journal = {Journal of Structural Integrity and Maintenance},
pages = {136--150},
title = {A novel approach for deterioration and damage identification in building structures based on Stockwell-Transform and deep convolutional neural network},
url = {http://dx.doi.org/10.1080/24705314.2021.2018840},
volume = {7},
year = {2022}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - In this paper, a novel deterioration and damage identification procedure (DIP) is presented and applied to building models. The challenge associated with applications on these types of structures is related to the strong correlation of responses, an issue that gets further complicated when coping with real ambient vibrations with high levels of noise. Thus, a DIP is designed utilizing low-cost ambient vibrations to analyze the acceleration responses using the Stockwell transform (ST) to generate spectrograms. Subsequently, the ST outputs become the input of two series of Convolutional Neural Networks (CNNs) established for identifying deterioration and damage on the building models. To the best of our knowledge, this is the first time that both damage and deterioration are evaluated on building models through a combination of ST and CNN with high accuracy.
AU  - Gharehbaghi,VR
AU  - Kalbkhani,H
AU  - Farsangi,EN
AU  - Yang,TY
AU  - Nguyen,A
AU  - Mirjalili,S
AU  - Malaga-Chuquitaype,C
DO  - 10.1080/24705314.2021.2018840
EP  - 150
PY  - 2022///
SN  - 2470-5314
SP  - 136
TI  - A novel approach for deterioration and damage identification in building structures based on Stockwell-Transform and deep convolutional neural network
T2  - Journal of Structural Integrity and Maintenance
UR  - http://dx.doi.org/10.1080/24705314.2021.2018840
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000768542300006&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - https://www.tandfonline.com/doi/full/10.1080/24705314.2021.2018840
VL  - 7
ER  -
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