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Damage Identification of a Steel Frame Based on Integration of Time Series and Neural Network under Varying Temperatures
Joint Authors
Huang, Minshui
Gu, Jianfeng
Lei, Yongzhi
Zhao, Wei
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-08-17
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Abstract EN
The effect of varying temperatures is one of the most important challenges of vibration-based damage identification due to its bigger effects on the structural response than the damage itself.
This study presents a methodology incorporating the autoregressive (AR) time series model with two-step artificial neural networks (ANNs) to identify damage under temperature variations.
AR coefficients, which are extracted by fitting the AR models to acceleration responses, are however sensitive to temperature changes, resulting in false diagnoses.
Thus, two-step ANN models with the inputs of difference in AR coefficients are utilized to compensate the detrimental temperature variations.
Finite element (FE) models of a steel-braced frame structure, simulating several damage scenarios with different damage locations and severities at fluctuating temperatures, are used to verify the effectiveness and reliability of this approach.
Numerical results indicate that the proposed approach could successfully recognize, locate, and quantify damage by using output-only vibration and temperature data regardless of varying temperatures and noise perturbations.
American Psychological Association (APA)
Huang, Minshui& Zhao, Wei& Gu, Jianfeng& Lei, Yongzhi. 2020. Damage Identification of a Steel Frame Based on Integration of Time Series and Neural Network under Varying Temperatures. Advances in Civil Engineering،Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1121592
Modern Language Association (MLA)
Huang, Minshui…[et al.]. Damage Identification of a Steel Frame Based on Integration of Time Series and Neural Network under Varying Temperatures. Advances in Civil Engineering No. 2020 (2020), pp.1-15.
https://search.emarefa.net/detail/BIM-1121592
American Medical Association (AMA)
Huang, Minshui& Zhao, Wei& Gu, Jianfeng& Lei, Yongzhi. Damage Identification of a Steel Frame Based on Integration of Time Series and Neural Network under Varying Temperatures. Advances in Civil Engineering. 2020. Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1121592
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1121592