Implementation of fiber-optic sensing systems in structural health monitoring of concrete
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Implementation of fiber-optic sensing systems in structural health monitoring of concrete
Nurzhigit Smailov, Akmaral Tolemanova, Amir Aziskhan, Beibarys Sekenov, Akezhan Sabibolda73-76
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Abstract
The study explores various fiber-optic sensing approaches, focusing on their application, implementation, and performance assessment for monitoring the structural health of concrete frameworks. It emphasizes the use of single-mode optical fibers due to their effectiveness in detecting microcracks, deformations, and temperature shifts in reinforced concrete. The investigation involved analyzing changes in optical characteristics through tests utilizing fiber Bragg grating (FBG) sensors embedded within concrete specimens exposed to mechanical loads and temperature fluctuations. Both graphical and quantitative analyses demonstrate that fiber-optic sensors enable real-time monitoring of stress and strain in concrete with high microstrain-level accuracy. Simulation work conducted using MATLAB confirmed the sensors’ responsiveness and long-term stability, particularly in detecting structural changes resulting from thermal effects and mechanical stress. Additionally, the thermal behavior of the sensors was examined using laser-based measurement systems in conjunction with Peltier modules. The research contributes to the advancement of intelligent SHM systems, aiming to enhance the durability and safety of civil infrastructure, especially in seismically active regions.
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References
[1] Abdykadyrov A., et al.: Optimization of Distributed Acoustic Sensors Based on Fiber Optic Technologies. Eastern-European Journal of Enterprise Technologies 5(131), 2024, 50–59 [https://doi.org/10.15587/1729-4061.2024.313455]. DOI: https://doi.org/10.15587/1729-4061.2024.313455
[2] Afzal M. H. B., et al.: Fiber Optic Sensor-Based Concrete Structural Health Monitoring. Saudi International Electronics, Communications and Photonics Conference – SIECPC, Riyadh, Saudi Arabia, 2011, 1–5 [https://doi.org/10.1109/SIECPC.2011.5876903]. DOI: https://doi.org/10.1109/SIECPC.2011.5876903
[3] Bado M. F., Casas J. R.: A Review of Recent Distributed Optical Fiber Sensors Applications for Civil Engineering Structural Health Monitoring. Sensors 21(5), 2021, 1818 [https://doi.org/10.3390/s21051818]. DOI: https://doi.org/10.3390/s21051818
[4] Banerji P., et al.: Application of Fiber-Optic Strain Sensors for Monitoring of a Pre-Stressed Concrete Box Girder Bridge. IEEE Sensors Conference, Limerick, Ireland, 2011, 1345–1348 [https://doi.org/10.1109/ICSENS.2011.6127255]. DOI: https://doi.org/10.1109/ICSENS.2011.6127255
[5] Barrias A., et al.: Embedded Distributed Optical Fiber Sensors in Reinforced Concrete Structures – A Case Study. Sensors 18(4), 2018, 980 [https://doi.org/10.3390/s18040980]. DOI: https://doi.org/10.3390/s18040980
[6] Bremer K., et al.: Fibre Optic Sensors for the Structural Health Monitoring of Building Structures. Procedia Technology 26, 2016, 524–529 [https://doi.org/10.1016/j.protcy.2016.08.065]. DOI: https://doi.org/10.1016/j.protcy.2016.08.065
[7] Halim M. I., et al.: Implementation of an Optical Fiber Sensor System to Monitor the Response of Reinforced Concrete due to Formwork Removal. IEEE AFRICON, Accra, Ghana, 2019, 1–5 [https://doi.org/10.1109/AFRICON46755.2019.9133856]. DOI: https://doi.org/10.1109/AFRICON46755.2019.9133856
[8] Herbers M., Richter B., Marx S.: Rayleigh-based crack monitoring with distributed fiber optic sensors: Experimental study on the interaction of spatial resolution and sensor type. Journal of Civil Structural Health Monitoring 15, 2025, 1439–1463 [https://doi.org/10.1007/s13349-024-00896-5]. DOI: https://doi.org/10.1007/s13349-024-00896-5
[9] Khadour A., Waeytens J.: Monitoring of Concrete Structures with Optical Fiber Sensors. Pacheco-Torgal F., et al. (eds.): Eco-Efficient Repair and Rehabilitation of Concrete Infrastructures. Woodhead Publishing, 2018, 97–121 [https://doi.org/10.1016/B978-0-08-102181-1.00005-8]. DOI: https://doi.org/10.1016/B978-0-08-102181-1.00005-8
[10] Khotiaintsev S., et al.: Structural Health Monitoring of Concrete Elements with Embedded Arrays of Optical Fibers. Proc. SPIE 8695, 2013 [https://doi.org/10.1117/12.2009851]. DOI: https://doi.org/10.1117/12.2009851
[11] López-Higuera J. M., et al.: Fiber Optics in Structural Health Monitoring. Proc. SPIE 7853, 2010 [https://doi.org/10.1117/12.876192]. DOI: https://doi.org/10.1364/OFC.2010.OWL4
[12] Mendes J. P., et al.: Low-cost versatile optical fiber sensor for structural health monitoring. Proc. SPIE 13639, 2025, 136397E [https://doi.org/10.1117/12.3062861]. DOI: https://doi.org/10.1117/12.3062861
[13] Sante R.: Fibre Optic Sensors for Structural Health Monitoring of Aircraft Composite Structures: Recent Advances and Applications. Sensors 15(8), 2015, 18666–18713 [https://doi.org/10.3390/s150818666]. DOI: https://doi.org/10.3390/s150818666
[14] Sekenov B., et al.: Fiber-Optic Temperature Sensors for Monitoring the Influence of the Space Environment on Nanosatellites: A Review. Mechanisms and Machine Science 167, 2024, 371–380 [https://doi.org/10.1007/978-3-031-67569-0_42]. DOI: https://doi.org/10.1007/978-3-031-67569-0_42
[15] Smailov N., et al.: Modelling and Application of Fibre Optic Sensors for Concrete Structures: A Literature Review. Civil Engineering and Architecture 13, 2025, 1885–1897 [https://doi.org/10.13189/cea.2025.130332]. DOI: https://doi.org/10.13189/cea.2025.130332
[16] Theodosiou A., et al.: In-Situ Relative Humidity Sensing for Ultra-High-Performance Concrete Using Polymer Fiber Bragg Gratings. IEEE Sensors Journal 21(14), 2021, 16086–16092 [https://doi.org/10.1109/JSEN.2021.3075609]. DOI: https://doi.org/10.1109/JSEN.2021.3075609
[17] Waeytens J., et al.: Model Updating Techniques for Damage Detection in Concrete Beam Using Optical Fiber Strain Measurement Device. Engineering Structures 129, 2016, 2–10 [https://doi.org/10.1016/j.engstruct.2016.08.004]. DOI: https://doi.org/10.1016/j.engstruct.2016.08.004
[18] Wójcik W., et al.: Research of parameters of fiber-optical measuring systems. Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska – IAPGOS 9(2), 2019, 28–31 [https://doi.org/10.5604/01.3001.0013.2543]. DOI: https://doi.org/10.5604/01.3001.0013.2543
[19] Yu C. B., et al.: Highly Sensitive Fiber-Optic Fabry-Perot Geophone with Graphene-Coated PMMA Membrane. 25th Optical Fiber Sensors Conference – OFS, Jeju, South Korea, 2017, 1–4 [https://doi.org/10.1117/12.2265299]. DOI: https://doi.org/10.1117/12.2265299
[20] Zilgarayeva A., et al.: Optical Sensor to Improve the Accuracy of Non-Invasive Blood Sugar Monitoring. Indonesian Journal of Electrical Engineering and Computer Science 34(3), 2024, 1489–1498 [https://doi.org/10.11591/ijeecs.v34.i3.pp1489-1498]. DOI: https://doi.org/10.11591/ijeecs.v34.i3.pp1489-1498
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