An improved version of mode shape based indicator for structural damage identification
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Từ khóa:
Gapped smooth method, modal properties, damage identification, AGTO
Tóm tắt
Damage detection is crucial for the operation and maintenance of an existing bridge or building. A vibration-based method is a popular approach that can be used to identify failures based on changes in the dynamic properties. However, this approach often requires information on both healthy and unhealthy states. In this current study, the structural failure determination is carried out through a damage index based solely on the unhealthy state. A combination of the gapped smooth and modal curvature methods is the core of calculating the proposed indicator. In particular, damage scenarios by means of assumed stiffness reduction, and cuts are investigated. Three categories of beam-like structures consisting of a simply supported beam, a cantilever beam, and a free-free beam are used to validate the applicability of the proposed approach. For comparison purposes, the traditional gapped smooth method is implemented. The location of damage can be identified using only displacement mode shapes. Then, damage quantification at the identified location is estimated using a stochastic optimization process. The promising findings indicate that the proposed approach can enhance the effectiveness of damage identification based on vibration data in the unhealthy state of the structuresTài liệu tham khảo
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[16]. D. H. Nguyen, Q. B. Nguyen, T. Bui-Tien, G. De Roeck, M. Abdel Wahab, Damage detection in girder bridges using modal curvatures gapped smoothing method and Convolutional Neural Network: Application to Bo Nghi bridge, Theoretical and Applied Fracture Mechanics, 109 (2020) 102728. https://doi: 10.1016/j.tafmec.2020.102728
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[18]. B. Abdollahzadeh, F. S. Gharehchopogh, S. Mirjalili, Artificial gorilla troops optimizer: A new nature‐inspired metaheuristic algorithm for global optimization problems, Int J Intell Syst, 36 (2021) 5887–5958. https://doi: 10.1002/int.22535
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[2]. O. Avci, O. Abdeljaber, S. Kiranyaz, M. Hussein, M. Gabbouj, D. J. Inman, A review of vibration-based damage detection in civil structures: From traditional methods to Machine Learning and Deep Learning applications, Mechanical Systems and Signal Processing, 147 (2021) 107077. https://doi: 10.1016/j.ymssp.2020.107077
[3].M. M. Abdel Wahab, G. De Roeck, Damage detection in bridges using modal curvatures: application to a real damage scenario, Journal of Sound and Vibration, 226 (1999) 217–235. https://doi: 10.1006/jsvi.1999.2295
[4]. Y. Yang, Y. Zhang, X. Tan, Review on Vibration-Based Structural Health Monitoring Techniques and Technical Codes, Symmetry, 13 (2021) 1998. https://doi: 10.3390/sym13111998
[5]. A. Khatir et al., A new hybrid PSO-YUKI for double cracks identification in CFRP cantilever beam, Composite Structures, 311 (2023) 116803. https://doi: 10.1016/j.compstruct.2023.116803
[6]. L. Ngoc-Nguyen et al., Damage assessment of suspension footbridge using vibration measurement data combined with a hybrid bee-genetic algorithm, Sci Rep, 12 (2022) 20143. https://doi: 10.1038/s41598-022-24445-6
[7]. H. Tran-Ngoc et al., Damage assessment in structures using artificial neural network working and a hybrid stochastic optimization, Sci Rep, 12 (2022) 4958. https://doi: 10.1038/s41598-022-09126-8
[8]. L. V. Ho, T. Bui-Tien, M. Abdel Wahab, Application of Gorilla Troops’ Social Intelligence in Damage Detection for a Girder Bridge, in Proceedings of the 5th International Conference on Numerical Modelling in Engineering, M. Abdel Wahab, Ed., Singapore: Springer Nature Singapore, (2023) 11–30. https://doi: 10.1007/978-981-19-8429-7_2
[9]. L. V. Ho, T. T. Trinh, G. De Roeck, T. Bui-Tien, L. Nguyen-Ngoc, M. Abdel Wahab, An efficient stochastic-based coupled model for damage identification in plate structures, Engineering Failure Analysis, 131 (2022) 105866. https://doi: 10.1016/j.engfailanal.2021.105866
[10]. A. K. Pandey, M. Biswas, M. M. Samman, Damage detection from changes in curvature mode shapes, Journal of Sound and Vibration, 145 (1991) 321–332. https://doi: 10.1016/0022-460X(91)90595-B
[11]. S. Khatir, S. Tiachacht, C. Le Thanh, H. Tran-Ngoc, S. Mirjalili, M. Abdel Wahab, A new robust flexibility index for structural damage identification and quantification, Engineering Failure Analysis, 129 (2021) 105714. https://doi: 10.1016/j.engfailanal.2021.105714
[12]. L. V. Ho et al., A hybrid computational intelligence approach for structural damage detection using marine predator algorithm and feedforward neural networks, Computers & Structures, 252 (2021) 106568. https://doi: 10.1016/j.compstruc.2021.106568
[13]. L. V. Ho, D. H. Nguyen, G. de Roeck, T. Bui-Tien, M. A. Wahab, Damage detection in steel plates using feed-forward neural network coupled with hybrid particle swarm optimization and gravitational search algorithm, J. Zhejiang Univ. Sci. A, 22 (2021) 467–480. https://doi: 10.1631/jzus.A2000316
[14]. C. P. Ratcliffe, Damage detection using a modified laplacian operator on mode shape data, Journal of Sound and Vibration, 204 (1997). https://doi: 10.1006/jsvi.1997.0961
[15]. M. K. Yoon, D. Heider, J. W. Gillespie, C. P. Ratcliffe, R. M. Crane, Local damage detection using the two-dimensional gapped smoothing method, Journal of Sound and Vibration, 279 (2005) 119–139. https://doi: 10.1016/j.jsv.2003.10.058
[16]. D. H. Nguyen, Q. B. Nguyen, T. Bui-Tien, G. De Roeck, M. Abdel Wahab, Damage detection in girder bridges using modal curvatures gapped smoothing method and Convolutional Neural Network: Application to Bo Nghi bridge, Theoretical and Applied Fracture Mechanics, 109 (2020) 102728. https://doi: 10.1016/j.tafmec.2020.102728
[17]. D. H. Nguyen, M. Abdel Wahab, Damage detection in slab structures based on two-dimensional curvature mode shape method and Faster R-CNN, Advances in Engineering Software, 176 (2023) 103371. https://doi: 10.1016/j.advengsoft.2022.103371
[18]. B. Abdollahzadeh, F. S. Gharehchopogh, S. Mirjalili, Artificial gorilla troops optimizer: A new nature‐inspired metaheuristic algorithm for global optimization problems, Int J Intell Syst, 36 (2021) 5887–5958. https://doi: 10.1002/int.22535
[19]. ANSYS, Inc. Southpointe, 275 Technology Drive, Canonsburg, PA 15317, Release 17.2, 2016
[20]. L. Ho Viet, T. Trinh Thi, B. Ho Xuan, Swarm intelligence-based technique to enhance performance of ANN in structural damage detection, 73 (2022) 1–15. https://doi: 10.47869/tcsj.73.1.1
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Nhận bài
20/08/2023
Nhận bài sửa
12/09/2023
Chấp nhận đăng
12/09/2023
Xuất bản
15/09/2023
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Kiểu trích dẫn
Ho Viet, L., Ho Vinh, H., Vu Van, T., & Ho Xuan, B. (1694710800). An improved version of mode shape based indicator for structural damage identification. Tạp Chí Khoa Học Giao Thông Vận Tải, 74(7), 790-804. https://doi.org/10.47869/tcsj.74.7.3
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