Abstract
Structural Health Monitoring (SHM) aims to promptly detect defects and damage that affect the safety and operational quality of structures. Monitoring data helps to make timely and appropriate maintenance plans to maintain the safe working ability and efficient exploitation of the structure during its service life. SHM has been used for a long time in the aviation industry. Today, it is also applied to large scale structural systems, which is very important in modern construction. In Vietnam, SHM has been applied to a variety of structures such as large dams and large span bridges in recent decades. This study introduces an overview of some types of SHM being applied in Vietnam. Results of structural monitoring of actual projects, which are designed, deployed, installed, collected, analyzed and evaluated by the authors. The research contents of machine learning application for fault diagnosis, monitoring data processing are also introduced in this study.
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References
Moreu, F., Li, X., Li, S., Zhang, D.: Technical Specifications of Structural Health Monitoring for Highway Bridges: New Chinese Structural Health Monitoring Code (2018)
Farrar, C.R., Worden, K.: An introduction to structural health monitoring. Philos. Trans. A Math. Phys. Eng. Sci. 365, 303–315 (2007)
Xác định hệ số tương quan chuyển vị cho mục đính đánh giá sức khỏe công trình. Tuyển tập Hội nghị Khoa học và Công nghệ lần thứ 17, ISBN 978-604-82-1982-6
Thành, T.P., et al.: Nghiên cứu quan trắc ứng suất - biến dạng cầu vòm nhịp lớn trong quá trình thi công sử dụng hệ thống cảm biến dây rung ở Việt Nam. Tạp Chí Khoa Học Công Nghệ Xây Dựng (KHCNXD) – ĐHXDHN 15(7V), 13–25 (2021). https://doi.org/10.31814/stce.huce(nuce)2021-15(7V)-02
Aravinda, S.R., et al.: Real-time monitoring of construction sites: sensors, methods, and applications. Autom. Constr. 136, 104099 (2022). https://doi.org/10.1016/j.autcon.2021.104099. ISSN 0926-5805
Jung, S., Kang, H., Sung, S. Hong, T.: Health risk assessment for occupants as a decision-making tool to quantify the environmental effects of particulate matter in construction projects. Build. Env. 161, 106267 (2019). ISSN 0360-1323
Ya-Lan, H., Liang, C.: A nonlinear hybrid wind speed forecasting model using LSTM network, hysteretic ELM and differential evolution algorithm. Energy Convers. Manag. (2018)
Kingma, D.P., Ba, J.: Adam: a method for stochastic optimization. In: Proceedings of the 3rd International Conference on Learning Representations (ICLR), San Diego (2015)
Goodfellow, Bengio, I., Courville, Y.: Deep Learning (Adaptive Computation and Machine Learning series). The MIT Press (2016). ISBN-10: 0262035618
Khatir, A., et al.: A new hybrid PSO-YUKI for double cracks identification in CFRP cantilever beam. Compos. Struct. 311, 116803 (2023). https://doi.org/10.1016/j.compstruct.2023.116803
Khatir, A., Tehami, M.: Finite element analysis of local buckling of steel-concrete continuous composite beams. In: Proceeding of the 2015 Congress on Advanced in Structural Engineering and Mechanics (ASEM 2015). https://doi.org/10.13140/RG.2.1.2107.5606
Khatir, A., Tehami, M., Khatir, S., Abdel Wahab, M.: Multiple damage detection and localization in beam-like and complex structures using co-ordinate modal assurance criterion combined with firefly and genetic algorithms. J. Vibroeng. 20(1), 832–842 (2018). https://doi.org/10.21595/jve.2016.19719. Republished Paper
Bettucci, E., Capozucca, R., Khatir, A., Khatir, S., Magagnini, E.: Concrete plates reinforced with embedded CFRP rods and carbon/steel strips. In: Capozucca, R., Khatir, S., Milani, G. (eds.) Proceedings of the International Conference of Steel and Composite for Engineering Structures. ICSCES 2022. LNCE, vol. 317. Springer, Cham (2023). https://doi.org/10.1007/978-3-031-24041-6_6
Khatir, A., Capozucca, R., Khatir, S., Magagnini, E.: Vibration-based crack prediction on a beam model using hybrid butterfly optimization algorithm with artificial neural network. Front. Struct. Civ. Eng. 16(8), 976–989 (2022). https://doi.org/10.1007/s11709-022-0840-2
Achouri, F., Khatir, A., Smahi, Z., Capozucca, R., Ouled Brahim, A.: Structural health monitoring of beam model based on swarm intelligence-based algorithms and neural networks employing FRF. J. Braz. Soc. Mech. Sci. Eng. 45(12), 621 (2023). https://doi.org/10.1007/s40430-023-04525-y
Khatir, A., Capozucca, R., Magagnini, E., Khatir, S., Bettucci, E.: Structural health monitoring for RC beam based on RBF neural network using experimental modal analysis. In: Capozucca, R., Khatir, S., Milani, G. (eds.) Proceedings of the International Conference of Steel and Composite for Engineering Structures. ICSCES 2022. LNCE, vol. 317, pp. 82–92. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-24041-6_7
Nguyen, L., Pham, H.H.: Health monitoring system for long span bridges across the Han River in Da Nang City, Vietnam. In: Bui, T.Q., Cuong, L.T., Khatir, S. (eds.) Structural Health Monitoring and Engineering Structures. LNCE, vol. 148, pp. 381–397. Springer, Singapore (2021). https://doi.org/10.1007/978-981-16-0945-9_31
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Lan, N., Hau, N.N., Kien, L.T., Cuong-Le, T. (2024). Structural Health Monitoring, Real Applications of Bridges in Vietnam. In: Benaissa, B., Capozucca, R., Khatir, S., Milani, G. (eds) Proceedings of the International Conference of Steel and Composite for Engineering Structures. ICSCES 2023. Lecture Notes in Civil Engineering, vol 486. Springer, Cham. https://doi.org/10.1007/978-3-031-57224-1_26
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