Selected issues concerning fibre-optic bending sensors

Les Hotra; Jacek Klimek; Ihor Helzhynskyy; Oksana Boyko; Svitlana Kovtun

doi:10.35784/iapgos.8681

Open full text

PDF

Published: Dec 20, 2025

DOI: https://doi.org/10.35784/iapgos.8681

Issue Vol. 15 No. 4 (2025)

Articles

Control of the magnetic levitation using a PID controller with adaptation based on linear interpolation logic and genetic algorithm
Dominik Fila, Andrzej Neumann, Bartosz Olesik, Jakub Pawelec, Kamil Przybylak, Mateusz Ungier, Dawid Wajnert

5-9
Development of a system for predicting failures of bagging machines
Nataliia Huliieva, Nataliia Lishchyna, Viktoriya Pasternak, Zemfira Huliieva

10-13
Development and verification of a modular object-oriented fuzzy logic controller architecture for customizable and embedded applications
Rahim Mammadzada

14-24
Mechanical fracture energy and structural-mechanical properties of meat snacks with beekeeping additives
Artem Antoniv, Igor Palamarchuk, Leonora Adamchuk, Marija Zheplinska

25-31
Modelling of dynamic processes in a nonholonomic system in the form of Gibbs-Appell equations on the example of a ball mill
Volodymyr Shatokhin, Yaroslav Ivanchuk, Vitaly Liman, Sergii Komar, Oleksii Kozlovskyi

32-38
Real-time Covid-19 diagnosis on embedded IoT platforms
Elmehdi Benmalek, Wajih Rhalem, Atman Jbari, Abdelilah Jilbab, Jamal Elmhamdi

39-45
Hybrid models for handwriting-based diagnosis of Parkinson's disease
Asma Ouabd, Achraf Benba, Abdelilah Jilbab, Ahmed Hammouch

46-50
Computer system for diagnostic and treatment of unilateral neglect syndrome
Krzysztof Strzecha, Agata Bukalska-Strzecha, Krzysztof Kurzdym, Dominik Sankowski

51-55
Informatics and measurement in healthcare: deep learning for diabetic patient readmission prediction
Shiva Saffari, Mahdi Bahaghighat

56-64
Optimization of non-invasive glucose monitoring accuracy using an optical sensor
Nurzhigit Smailov, Aliya Zilgarayeva, Sergii Pavlov, Balzhan Turusbekova, Akezhan Sabibolda

65-70
Stochastic multi-objective minimax optimization of combined electromagnetic shield based on three-dimensional modeling of overhead power lines magnetic field
Borys Kuznetsov, Tatyana Nikitina, Alexander Kutsenko, Ihor Bovdui, Kostiantyn Czunikhin, Olena Voloshko, Roman Voliansky, Viktoriia Ivannikova

71-75
Advanced energy management strategies for AC/DC microgrids
Zouhir Boumous, Samira Boumous, Tawfik Thelaidjia

76-82
Experimental study of a multi-stage converter circuit
Kyrmyzy Taissariyeva, Kuanysh Muslimov, Yerlan Tashtay, Gulim Jobalayeva, Lyazzat Ilipbayeva, Ingkar Issakozhayeva, Akezhan Sabibolda

83-86
Deep learning-based prediction of structural parameters in FDTD-simulated plasmonic nanostructures
Shahed Jahidul Haque, Arman Mohammad Nakib

87-94
Development of an algorithm for calculating ion exchange processes using the Python ecosystem
Iryna Chub, Oleksii Proskurnia, Kateryna Demchenko, Oleksandr Miroshnyk, Taras Shchur, Serhii Halko

95-99
Intelligent model for reliability control and safety in urban transport systems
Anastasiia Kashkanova, Alexander Rotshtein, Andrii Kashkanov, Denis Katelnikov

100-107
Analysis of the interaction of components of a modular parcel storage system using UML diagrams
Lyudmila Samchuk, Yuliia Povstiana, Anastasia Hryshchuk

108-116
Evaluating modified pairing insertion heuristics for efficient dial-a-ride problem solutions in healthcare logistics
Rodolfo Eleazar Pérez Loaiza, Aaron Guerrero-Campanur, Edmundo Bonilla Huerta

117-123
Analysis of modern tools, methods of audit and monitoring of database security
Kateryna Mykhailyshyn, Oleh Harasymchuk, Oleh Deineka, Yurii Dreis, Volodymyr Shulha, Yuriy Pepa

124-129
Improving underwater visuals by fusion of Deep-Retinex and GAN for enhanced image quality in subaquatic environments
Anuradha Chinta, Bharath Kumar Surla, Chaitanya Kodali

130-136
The mathematical method for assessing the cybersecurity state of cloud services
Yevheniia Ivanchenko, Volodymyr Shulha, Ihor Ivanchenko, Yevhenii Pedchenko, Mari Petrovska

137-141
Evaluation of the performance of LLMs deployments in selected cloud-based container services
Mateusz Stęgierski, Piotr Szpak, Sławomir Przyłucki

142-150
Implementing traits in C# using Roslyn Source Generators
Mykhailo Pozur, Viktoria Voitko, Svitlana Bevz, Serhii Burbelo, Olena Kosaruk

151-157
Impact of customizable orchestrator scheduling on machine learning efficiency in edge environments
Konrad Cłapa, Krzysztof Grudzień, Artur Sierszeń

158-163
Reconfigured CoARX architecture for implementing ARX hashing in microcontrollers of IoT systems with limited resources
Serhii Zabolotnii, Inna Rozlomii, Andrii Yarmilko, Serhii Naumenko

164-169
Integral assessment of the spring water quality with the use of fuzzy logic toolkit
Vyacheslav Repeta, Oleksandra Krykhovets, Yurii Kukura

170-176
Selected issues concerning fibre-optic bending sensors
Les Hotra, Jacek Klimek, Ihor Helzhynskyy, Oksana Boyko, Svitlana Kovtun

177-181

DOI

https://doi.org/10.35784/iapgos.8681

Authors

Les Hotra

les.m.hotra@lpnu.ua

Lviv Polytechnic National University, Department of Electronic Engineering, Ukraine

https://orcid.org/0009-0005-1351-1883

Jacek Klimek

j.klimek@pollub.pl

Lublin University of Technology, Poland

https://orcid.org/0000-0001-8141-6136

Ihor Helzhynskyy

iigorg@ukr.net

Lviv Polytechnic National University, Ukraine

Oksana Boyko

oxana_bojko@ukr.net

Danylo Halytsky Lviv National Medical University, Ukraine

Svitlana Kovtun

KovtunSI@nas.gov.ua

General Energy Institute of National Academy of Sciences of Ukraine, Ukraine

Abstract

This paper presents a comprehensive review of bending sensors and their classifications. The main focus is on advancements in the design of optical fibre bending sensors based on fibre Bragg gratings (FBGs). Various measurement principles employed in optical fibre bending sensors are analysed, highlighting their respective advantages and limitations. Particular attention is given to sensors utilising long period gratings (LPGs), Tilted fibre Bragg gratings (TFBGs), and multicore (MCF) fibre structures, which demonstrate significant potential for the development of highly sensitive and compact bending sensing systems.

Keywords:

optical fibre, bending sensor, Fibre Bragg Grating, Long Period Grating, tilted Fibre Bragg Grating, multicore fibre sensor

References

[1] Amorebieta J. et al.: Compact omnidirectional multicore fiber-based vector bending sensor. Sci Rep 11, 2021, 5989 [https://doi.org/10.1038/s41598-021-85507-9].

[2] Barrera D., Madrigal J., Sales S.: Long Period Gratings in Multicore Optical Fibers for Directional Curvature Sensor Implementation. Journal of Lightwave Technology 36(4), 2018, 1063–1068 [https://doi.org/10.1109/JLT.2017.2764951].

[3] Chen Y. et al.: Experimental study on temperature-insensitive curvature sensor based on reflective all-fiber structure. Infrared Physics & Technology 137, 2024, 105146 [https://doi.org/10.1016/j.infrared.2024.105146].

[4] Exploring FBG Tilt Sensor Market Disruption and Innovation. DiMarket. [https://www.datainsightsmarket.com/reports/fbg-tilt-sensor-1670260#].

[5] Fazzi L.: Minimal Intrusive Multi-parameter Optical Fibre Sensor for Aerospace Structures and Adhesives. Dissertation, Delft University of Technology [https://doi.org/10.4233/uuid:6bbb0c33-97b7-415e-9649-9e0d7f4117de].

[6] Fiber Bragg Grating Sensor Market Size & Share Analysis – Growth Trends and Forecast (2025–2030) Mordor Intelligence [https://www.mordorintelligence.com/industry-reports/fiber-bragg-grating-sensor-market].

[7] Harasim D.: Temperature-insensitive bending measurement method using optical fiber sensors. Sensors and Actuators A: Physical 332/2021, 113207 [https://doi.org/10.1016/j.sna.2021.113207].

[8] Kisała P.: Physical foundations determining spectral characteristics measured in Bragg gratings subjected to bending. Metrol. Meas. Syst. 29(3), 2022, 573–584 [https://doi.org/10.1016/j.sna.2021.113207].

[9] Kok S. P. et al.: Advances in Fiber Bragg Grating (FBG) Sensing: A Review of Conventional and New Approaches and Novel Sensing Materials in Harsh and Emerging Industrial Sensing. IEEE Sensors Journal 24(19), 2024, 29485–29505 [https://doi.org/10.1109/jsen.2024.3434351].

[10] Li Y. et al.: Temperature-insensitive vector curvature sensor based on four-core fiber offset structure, Infrared Physics & Technology 140, 2024, 105368 [https://doi.org/10.1016/j.infrared.2024.105368].

[11] Liu Y. et al.: Investigations on seven-core fiber based interferometric all-fiber sensor for curvature and temperature measurements. Optik 254, 2022, 168638 [https://doi.org/10.1016/j.ijleo.2022.168638].

[12] Liu Z. et al.: Temperature-insensitive curvature sensor based on Bragg gratings written in strongly coupled multicore fiber. Opt. Lett. 46, 2021, 3933–3936 [https://doi.org/10.1364/OL.432889].

[13] Peng Y. et al.: Recent advances in flexible bending sensors and their applications. International Journal of Smart and Nano Materials 15(4), 2024, 697–729 [https://doi.org/10.1080/19475411.2024.2417834].

[14] Prisutova J. et al.: Use of Fibre-Optic Sensors for Pipe Condition and Hydraulics Measurements: A Review. Civil Eng. 3(1), 2022, 85–113 [https://doi.org/10.3390/civileng3010006].

[15] Valentín-Coronado L. M. et al.: Bending classification from interference signals of a fiber optic sensor using shallow learning and convolutional neural networks. Pattern Recognition Letters 186, 2024, 354–360 [https://doi.org/10.1016/j.patrec.2024.06.029].

[16] Wang H. et al.: Multi-parameter sensor based on cascaded multicore FBGs and an FPI for bending, temperature and pressure measurements. Optics & Laser Technology 175, 2024, 110782 [https://doi.org/10.1016/j.optlastec.2024.110782].

[17] Wang Q., Liu Y.: Review of optical fiber bending/curvature sensor. Measurement 130, 2018, 161–176.

[18] Xia Q. et al.: Research on fiber Bragg grating Fabry-Perots bending sensor based on principal component analysis. Optics Express 33(4), 2025, 8014–8026 [https://doi.org/10.1364/OE.546742].

[19] Xu M. et al.: High-sensitivity two-axis vector bending sensor based on side-grooved long period grating in eccentric core fiber. Optics & Laser Technology, 153, 2022, 108218 [https://www.sciencedirect.com/science/article/pii/S0030399222003759].

[20] Xu S., Chen H., Feng W.: Fiber-optic curvature and temperature sensor based on the lateral-offset spliced SMF-FCF-SMF interference structure. Optics & Laser Technology 141, 2021, 107174 [https://doi.org/10.1016/j.optlastec.2021.107174].

[21] Yang S. et al.: Highly Sensitive Bending Sensor Based on Multicore Optical Fiber With Diagonal Cores Reflector at the Fiber Tip. Journal of Lightwave Technology 40(17), 2022, 6030–6036 [https://doi.org/10.1109/JLT.2022.3184042].

[22] Yassin M. H. et al.: Fiber Bragg grating (FBG)-based sensors: a review of technology and recent applications in structural health monitoring (SHM) of civil engineering structures. Discov Civ Eng 1, 2024, 151 [https://doi.org/10.1007/s44290-024-00141-4].

[23] Zhang K. et al.: Simultaneous detection of vector bending and temperature using dual-core fiber cascaded FBG structure. Measurement 241, 2025, 115760 [https://doi.org/10.1016/j.measurement.2024.115760].

[24] Zhang S. et al.: All fiber compact bending sensor with high sensitivity based on a multimode fiber embedded chirped long-period grating. Opt. Lett. 45, 2020, 4172–4175 [https://doi.org/10.1364/OL.396301].

[25] Zhao Z, Dang Y, Tang M.: Advances in Multicore Fiber Grating Sensors. Photonics 9(6), 2022, 381 [https://doi.org/10.3390/photonics9060381].

[26] Zhou Y. et al.: High-sensitive bending sensor based on a seven-core fiber. Optics Communications 483, 2021, 126617.

Hotra, L., Klimek, J., Helzhynskyy, I., Boyko, O., & Kovtun, S. (2025). Selected issues concerning fibre-optic bending sensors. Informatyka, Automatyka, Pomiary W Gospodarce I Ochronie Środowiska, 15(4), 177–181. https://doi.org/10.35784/iapgos.8681

Selected issues concerning fibre-optic bending sensors

Issue Vol. 15 No. 4 (2025)

Archives

DOI

Authors

Abstract

Keywords:

References

License

Article Sidebar

Issue Vol. 15 No. 4 (2025)

Archives

Main Article Content

DOI

Authors

Abstract

Keywords:

References

Article Details

License