Deterioration and damage identification in building structures using a novel feature selection method

Article


Gharehbaghi, Vahid Reza, Farsangi, Ehsan Noroozinejad, Yang, T.Y. and Hajirasouliha, Iman. 2021. "Deterioration and damage identification in building structures using a novel feature selection method." Structures. 29, pp. 458-470. https://doi.org/10.1016/j.istruc.2020.11.040
Article Title

Deterioration and damage identification in building structures using a novel feature selection method

ERA Journal ID211389
Article CategoryArticle
AuthorsGharehbaghi, Vahid Reza (Author), Farsangi, Ehsan Noroozinejad (Author), Yang, T.Y. (Author) and Hajirasouliha, Iman (Author)
Journal TitleStructures
Journal Citation29, pp. 458-470
Number of Pages13
Year2021
PublisherElsevier
Place of PublicationUnited Kingdom
ISSN2352-0124
Digital Object Identifier (DOI)https://doi.org/10.1016/j.istruc.2020.11.040
Web Address (URL)https://www.sciencedirect.com/science/article/pii/S2352012420306810
Abstract

Identifying structural defects in complex structures is one of the main objectives in real-world structural health
monitoring (SHM) applications. In this article, a signal-based supervised methodology is proposed for detecting
deterioration and damage in building structures. This method benefits from a novel feature selection method called signal simulation-based feature selection (SSFS) algorithm, which only relies on baseline signals to extract the most sensitive features from any type of structure. The results showed that the offered methodology is capable of identifying damage and deterioration precisely, and therefore, can be a viable alternative to conventional techniques that require additional information

KeywordsDamage identification; Deterioration; SSFS algorithm; Structural Health Monitoring (SHM)
ANZSRC Field of Research 2020400506. Earthquake engineering
Byline AffiliationsKharazmi University, Iran
Graduate University of Advanced Technology, Iran
University of British Columbia, Canada
University of Sheffield, United Kingdom
Institution of OriginUniversity of Southern Queensland
Permalink -

https://research.usq.edu.au/item/q6y1y/deterioration-and-damage-identification-in-building-structures-using-a-novel-feature-selection-method

  • 119
    total views
  • 5
    total downloads
  • 1
    views this month
  • 0
    downloads this month

Export as

Related outputs

Robustness of Deep Transfer Learning-Based Crack Detection against Uncertainty in Hyperparameter Tuning and Input Data
Nguyen, Andy, Chianese, Riccardo R., Gharehbaghi, Vahid R., Perera, Ruveen, Low, Tobias, Aravinthan, Thiru, Yu, Yang, Samali, Bijan, Guan, Hong, Khuc, Tung and Le, Thach N.. 2022. "Robustness of Deep Transfer Learning-Based Crack Detection against Uncertainty in Hyperparameter Tuning and Input Data." Guan, Hong, Chan, Tommy H. T. and Li, Jianchun (ed.) Recent Advances in Structural Health Monitoring Research in Australia. New York, United States. Nova Science Publishers. pp. 215-243
A data-driven approach for linear and nonlinear damage detection using variational mode decomposition and GARCH model
Gharehbaghi, Vahid Reza, Kalbkhani, Hashem, Farsangi, Ehsan Noroozinejad, Yang, T. Y. and Mirjalili, Seyedali. 2023. "A data-driven approach for linear and nonlinear damage detection using variational mode decomposition and GARCH model." Engineering with Computers: an international journal for simulation-based engineering. 39 (3), pp. 2017-2034. https://doi.org/10.1007/s00366-021-01568-4
A computationally efficient crack detection approach based on deep learning assisted by stockwell transform and linear discriminant analysis
Nguyen, Andy, Nguyen, Canh Long, Gharehbaghi, Vahidreza, Perera, Ruveen, Brown, Jason, Yu, Yang and Kalbkhani, Hashem. 2022. "A computationally efficient crack detection approach based on deep learning assisted by stockwell transform and linear discriminant analysis." Structures. 45, pp. 1962-1970. https://doi.org/10.1016/j.istruc.2022.09.107
Influence of image noise on crack detection performance of deep convolutional neural networks
Chianese, R., Nguyen, A., Gharehbaghi, V. R., ‪Aravinthan‬, T. and Noori, M.. 2021. "Influence of image noise on crack detection performance of deep convolutional neural networks." Cunha, A. and Caetano, E. (ed.) 10th International Conference on Structural Health Monitoring of Intelligent Infrastructure: Advanced Research and Real-World Applications (SHMII-10). Porto, Portugal 30 Jun - 02 Jul 2021 Winnipeg, Canada.
Global best practices in dams & hydraulic structures: Alkali-Silica Reaction
Gharehbaghi, Vahid R. and Nguyen, Andy. 2021. "Global best practices in dams & hydraulic structures: Alkali-Silica Reaction." USHER in 2021: Redefining Resiliency in the New Normal. Philippines 23 Jul 2021
A Critical Review on Structural Health Monitoring: Definitions, Methods, and Perspectives
Gharehbaghi, Vahid Reza, Farsangi, Ehsan Noroozinejad, Noori, Mohammad, Yang, T. Y., Li, Shaofan, Nguyen, Andy, Malaga‑Chuquitaype, Christian, Gardoni, Paolo and Mirjalili, Seyedali. 2021. "A Critical Review on Structural Health Monitoring: Definitions, Methods, and Perspectives." Archives of Computational Methods in Engineering. https://doi.org/10.1007/s11831-021-09665-9
Modified plate frame interaction method for evaluation of steel plate shear walls with beam-connected web plates
Mamazizi, Arman, Khani, Shafi, Gharehbaghi, V.R. and Farsangi, Ehsan Noroozinejad. 2022. "Modified plate frame interaction method for evaluation of steel plate shear walls with beam-connected web plates." Journal of Building Engineering. 45. https://doi.org/10.1016/j.jobe.2021.103682
Rehabilitation of SDOF systems under air blast loading with a modified negative stiffness amplifying damper
Kiran, K. K., Farsangi, Ehsan Noroozinejad, Gharehbaghi, Vahidreza and Bogdanovic, Aleksandra. 2022. "Rehabilitation of SDOF systems under air blast loading with a modified negative stiffness amplifying damper." Journal of Building Pathology and Rehabilitation. 7 (1). https://doi.org/10.1007/s41024-022-00178-x
An innovative methodology for hybrid vibration control (MR+TMD) of buildings under seismic excitations
Lavassani, Seyed Hossein Hosseini, Shangapour, Saman, Homami, Peyman, Gharehbaghi, Vahidreza, Farsangi, Ehsan Noroozinejad and Yang, T.Y.. 2022. "An innovative methodology for hybrid vibration control (MR+TMD) of buildings under seismic excitations." Soil Dynamics and Earthquake Engineering. 155. https://doi.org/10.1016/j.soildyn.2022.107175
Interpretation of simultaneously optimized fuzzy controller and active tuned mass damper parameters under Pulse-type ground motions
Lavassani, Seyed Hossein Hosseini, Ebadijalal, Mehrdad, Shahrouzi, Mohsen, Gharehbaghi, Vahidreza, Farsangi, Ehsan Noroozinejad and Yang, T.Y.. 2022. "Interpretation of simultaneously optimized fuzzy controller and active tuned mass damper parameters under Pulse-type ground motions." Engineering Structures. 261. https://doi.org/10.1016/j.engstruct.2022.114286
A novel approach for deterioration and damage identification in building structures based on Stockwell-Transform and deep convolutional neural network
Gharehbaghi, Vahid Reza, Kalbkhani, Hashem, Farsangi, Ehsan Noroozinejad, Yang, T.Y., Nguyen, Andy, Mirjalili, Seyedali and Malaga‑Chuquitaype, Christian. 2022. "A novel approach for deterioration and damage identification in building structures based on Stockwell-Transform and deep convolutional neural network." Journal of Structural Integrity and Maintenance. 7 (2), pp. 136-150. https://doi.org/10.1080/24705314.2021.2018840
Next Generation “Living” Laboratory for Engineering Education and Engagement
Nguyen, Andy, Le, Ngoc Thach, Landers, Richard, Byrne, Terry, McDougall, Kevin, Gharehbaghi, Vahid Reza, Brown, Jason, Nguyen, Canh Long and Karunasena, Warna. 2022. "Next Generation “Living” Laboratory for Engineering Education and Engagement." 33rd Annual Conference of the Australasian Association of Engineering Education (AAEE 2022). Sydney, Australia 04 - 07 Dec 2022 Australia.
Supervised damage and deterioration detection in building structures using an enhanced autoregressive time-series approach
Gharehbaghi, Vahid Reza, Nguyen, Andy, Farsangi, Ehsan Noroozinejad and Yang, T. Y.. 2020. "Supervised damage and deterioration detection in building structures using an enhanced autoregressive time-series approach." Journal of Building Engineering. 30, pp. 1-16. https://doi.org/10.1016/j.jobe.2020.101292