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Design of a Fiber Temperature and Strain Sensor Model Using a Fiber Bragg Grating to Monitor Road Surface Conditions
(Multidisciplinary Digital Publishing Institute, 2024-09-13)
Гулжан Кашаганова
;
Айнур Козбакова
;
Timur Kartbayev
;
Күлжан Тогжанова
;
Жулдыз Алимсеитова
In this paper, the types and principles of operation of fiber sensors based on fiber Bragg gratings (FBGs) are investigated. The influence of strain and temperature on the characteristics of FBGs is considered, and a method for the simultaneous measurement of these parameters is presented. Laboratory studies were carried out in the temperature range from +18 °C to +135 °C with an incremental step of 5 °C, with the actual temperature not deviating by more than ±0.5 °C. From the data obtained, the Bragg wavelength–temperature relationships were plotted, which showed a linear increase in wavelength with increasing temperature. This study shows that the use of two FBGs with a different sensitivity to temperature and strain allowed for the simultaneous measurement of both parameters. Numerical models created in the MATLAB R2022b environment confirmed the high accuracy and precision of the measurements. The FBG-based sensors demonstrated a robust performance in harsh environments, withstanding temperatures of up to 160 °C and high humidity, making them applicable in various industries and sciences. This work confirms that FBGs are a promising tool for accurate temperature and strain measurements, providing reliable results in harsh environments.
Цитирования (OpenAlex) 9Цитирования (OpenCitations) 7
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An Internet of Things-Based Multisensor Platform for Biogas Monitoring and Experimental Data Analysis
(Multidisciplinary Digital Publishing Institute, 2026-09-03)
Omirlan Auelbekov
;
Айнур Козбакова
;
Kairat Yessentayev
;
Kuanyshbek Igibayev
This article discusses the intelligent analysis of multisensory biogas data obtained from an experimental dataset generated by a Lab-on-Chip platform. The relevance of this work stems from the need for real-time monitoring of biogas quality and biomass condition under anaerobic digestion conditions, where changes in the concentrations of methane, carbon dioxide, hydrogen sulfide, oxygen, and temperature directly affect the stability of the technological process and the energy efficiency of the plant. This study utilizes a multisensor Lab-on-Chip/biosensor platform designed for rapid analysis of small samples of biogas, biomass, and biomix. The platform integrates gas, liquid, and optical sensor channels, as well as a module for transmitting data to the cloud. The experimental data obtained are processed using intelligent data analysis methods, including statistical analysis, correlation analysis, anomaly detection, and assessment of the relationships between monitored parameters. The scientific significance of this work lies in the application of an integrated approach to the analysis of multichannel experimental data obtained from the ESP32 microcontroller, which enables a more accurate and timely assessment of the state of the biogas process. The practical significance lies in the ability to use the proposed approach for remote monitoring, early detection of anomalies, and improving the efficiency of biogas plant management.

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