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Physics-Based Calibration of the Fiber Bragg Grating Temperature Response via Particle Swarm Optimization
Authors
1 2 Department of Physics, Faculty of Science, Universiti Teknologi Malaysia, Johor Bahru, Johor, Malaysia. 3 Department of Computer, Umaru Ali Shinkafi Polytechnic Sokoto, Nigeria.
Article Information
- Published In
- Volume 6, Issue 6 (2026)
- Published Online
- November-December 2026
- Pages
- 146-152
- Article Type
- Original Article
- Check for updates
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References
1. SAdhreena, M. S. N. A., Hafizi, Z. M., Vorathin, E., & Zahir, N. (2023). A study of fiber Bragg grating temperature sensor for under water temperature monitoring. Journal of Engineering and Technology, 14(1), 237-244.
2. Agliullin, T., Anfinogentov, V., Morozov, O., Sakhabutdinov, A., Valeev, B., Niyazgulyeva, A., & Garovov, Y. (2023). Comparative analysis of the methods for fiber Bragg structures spectrum modeling. Algorithms, 16(2), 101. https://doi.org/10.3390/a16020101
3. Erdogan, T. (1997). Fiber grating spectra. Journal of Lightwave Technology, 15(8), 1277-1294. https://doi.org/10.1109/50.618322
4. Hill, K. O., & Meltz, G. (1997). Fiber Bragg grating technology fundamentals and overview. Journal of Lightwave Technology, 15(8), 1263-1276. https://doi.org/10.1109/50.618320
5. Li, Y., Chen, T., Si, J., He, Y., Gao, B., & Hou, X. (2023). Application of a fiber Bragg grating temperature sensing method based on support vector regression optimized by a genetic algorithm for the decreasing external ambient temperature case. Applied Optics, 62(26), 7050-7057. https://doi.org/10.1364/AO.492971
6. Macheso, P. S., & Zekriti, M. (2024). Modeling and analysis of fiber Bragg grating temperature sensor for Internet of Things applications (FBG-4-IoT). International Journal of Intelligent Networks, 5, 224-230. https://doi.org/10.1016/j.ijin.2024.05.006
7. Pogorzelski, P., Anuszkiewicz, A., Buczyński, R., & Osuch, T. (2024). A numerical tool for spectral analysis of fiber Bragg gratings written in few-mode excited optical fibers. Acta Physica Polonica A, 146(4), 490-496. https://doi.org/10.12693/APhysPolA.146.490
8. Saha, S., Hadigheh, S. A., Rukhlenko, I., Valix, M., Uy, B., & Fleming, S. (2025). Machine learning-augmented multi-arrayed fiber Bragg grating sensors for enhanced structural health monitoring by discriminating strain and temperature variations. Journal of Civil Structural Health Monitoring, 15, 597-618. https://doi.org/10.1007/s13349-024-00827-4
9. Sahota, J. K., Gupta, N., & Dhawan, D. (2020). Fiber Bragg grating sensors for monitoring of physical parameters: A comprehensive review. Optical Engineering, 59(6), 060901. https://doi.org/10.1117/1.OE.59.6.060901
10. Shami, T. M., El-Saleh, A. A., Alswaitti, M., Al-Tashi, Q., Summakieh, M. A., & Mirjalili, S. (2022). Particle Swarm Optimization: A comprehensive survey. IEEE Access, 10, 10031-10061. https://doi.org/10.1109/ACCESS.2022.3142859.
11. Soman, R., Boyer, A., Kim, J. M., & Peters, K. (2022). Particle Swarm Optimization Algorithm for Guided Waves Based Damage Localization Using Fiber Bragg Grating Sensors in Remote Configuration. Sensors, 22(16), 6000. https://doi.org/10.3390/s22166000.
2. Agliullin, T., Anfinogentov, V., Morozov, O., Sakhabutdinov, A., Valeev, B., Niyazgulyeva, A., & Garovov, Y. (2023). Comparative analysis of the methods for fiber Bragg structures spectrum modeling. Algorithms, 16(2), 101. https://doi.org/10.3390/a16020101
3. Erdogan, T. (1997). Fiber grating spectra. Journal of Lightwave Technology, 15(8), 1277-1294. https://doi.org/10.1109/50.618322
4. Hill, K. O., & Meltz, G. (1997). Fiber Bragg grating technology fundamentals and overview. Journal of Lightwave Technology, 15(8), 1263-1276. https://doi.org/10.1109/50.618320
5. Li, Y., Chen, T., Si, J., He, Y., Gao, B., & Hou, X. (2023). Application of a fiber Bragg grating temperature sensing method based on support vector regression optimized by a genetic algorithm for the decreasing external ambient temperature case. Applied Optics, 62(26), 7050-7057. https://doi.org/10.1364/AO.492971
6. Macheso, P. S., & Zekriti, M. (2024). Modeling and analysis of fiber Bragg grating temperature sensor for Internet of Things applications (FBG-4-IoT). International Journal of Intelligent Networks, 5, 224-230. https://doi.org/10.1016/j.ijin.2024.05.006
7. Pogorzelski, P., Anuszkiewicz, A., Buczyński, R., & Osuch, T. (2024). A numerical tool for spectral analysis of fiber Bragg gratings written in few-mode excited optical fibers. Acta Physica Polonica A, 146(4), 490-496. https://doi.org/10.12693/APhysPolA.146.490
8. Saha, S., Hadigheh, S. A., Rukhlenko, I., Valix, M., Uy, B., & Fleming, S. (2025). Machine learning-augmented multi-arrayed fiber Bragg grating sensors for enhanced structural health monitoring by discriminating strain and temperature variations. Journal of Civil Structural Health Monitoring, 15, 597-618. https://doi.org/10.1007/s13349-024-00827-4
9. Sahota, J. K., Gupta, N., & Dhawan, D. (2020). Fiber Bragg grating sensors for monitoring of physical parameters: A comprehensive review. Optical Engineering, 59(6), 060901. https://doi.org/10.1117/1.OE.59.6.060901
10. Shami, T. M., El-Saleh, A. A., Alswaitti, M., Al-Tashi, Q., Summakieh, M. A., & Mirjalili, S. (2022). Particle Swarm Optimization: A comprehensive survey. IEEE Access, 10, 10031-10061. https://doi.org/10.1109/ACCESS.2022.3142859.
11. Soman, R., Boyer, A., Kim, J. M., & Peters, K. (2022). Particle Swarm Optimization Algorithm for Guided Waves Based Damage Localization Using Fiber Bragg Grating Sensors in Remote Configuration. Sensors, 22(16), 6000. https://doi.org/10.3390/s22166000.
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