The pulsed elongation of fiber Bragg gratings is considered in order to be used to measure the displacement or deformation rate of objects. Optimal measurement modes were determined, numerical simulation of the output signal was performed during pulsed elongation or compression of the fiber grating, and the main patterns were analyzed. The results of the application of the Bragg gratings for the experimental determination of the deformation rate of materials under pulsed magnetic action are presented. Experimentally obtained and theoretical dependencies are compared. The dependencies of the change in the grating parameters—the coefficient and the half-width of the reflection spectrum with successive shortening of the grating—are given.

The results of applications of various methods for measuring the parameters of high-speed loading using a strain gauge, a fiber Bragg grating located on a metal measuring rod and an interferometer monitoring the movement of the free boundary of the end of the rod are presented. Numerical simulation confirmed the adequacy of the description of the shock-wave process according to experimental data and showed that, with the thickness of the adhesive layer fixing the fiber Bragg grating and the strain gauge on a dimensional rod up to 100 µm, the deformation parameters of the sensors correspond to the parameters of the stress–strain state of the rod. Experimentally, a good correspondence of the results of measuring the magnitude of the relative deformation at a pulse duration of 10–100 µs using sensors of various types is shown, and an estimate of the limit values of the measured values of the deformation wave parameters is given.

The work is devoted to the consideration of methods for determining the strain of objects using fiber Bragg gratings under a high-frequency vibration or pulsed mechanical action, which is difficult to perform using widespread methods and devices. The methods are based on numerical processing of the time dependence of the radiation power reflected from the fiber Bragg grating at various wavelengths, which makes it possible to measure strain parameters in a wide range of magnitude and frequencies. The efficiency of the proposed methods is demonstrated by numerical simulation. It is shown that it is possible to restore the strain dependence on time in the range $\pm 1000$ $\mathsf{\mu }\mathsf{ϵ}$ or more from simultaneously measured power dependencies reflected by the fiber Bragg grating using common fiber-optic components. The case of sequential registration of reflected radiation power at different wavelengths to determine the probability density of the distribution of the strain values is also considered. The results of signal processing obtained both by numerical simulation and experimentally for the case of a linear vibration are presented. The technical problems of using the proposed methods are discussed.

This article presents a detailed analytical review of distributed acoustic sensing (DAS) systems for seismic monitoring, with emphasis on their optical infrastructure, signal processing methodologies, and integration with machine learning (ML) approaches. DAS leverages existing fiber-optic cables by utilizing Rayleigh backscattering to convert them into high-resolution seismic sensing networks. These networks offer spatial resolution down to one meter and can operate effectively over distances up to 250 kilometers in real time. The system’s responsiveness to pressure and environmental fluctuations has been captured through mathematical modeling. To enhance signal quality, seismic data is subjected to advanced processing techniques, including Fourier analysis, wavelet transformation, and adaptive noise filtering, yielding signal-to-noise improvements of up to 15 dB. In terms of data interpretation, machine learning models such as support vector machines (SVM), long short-term memory networks (LSTM), and gradient boosting classifiers have achieved high performance, often surpassing 90% accuracy in seismic event detection. Furthermore, scalable insights are supported through unsupervised and semi-supervised learning strategies. To address challenges related to model transparency, explainability tools like SHAP and LIME are applied to aid in the interpretation of predictive outputs. Field deployments of DAS systems, combined with intelligent analytics, demonstrate significant promise for large-scale seismic detection across both terrestrial and marine environments.

В статье рассматриваются возможности использования волоконно-оптических датчиков для диагностики состояния металлических и бетонных конструкций. Волоконно-оптические датчики привлекают внимание благодаря своей высокой чувствительности, невосприимчивости к электромагнитным помехам и устойчивости к суровым условиям окружающей среды. Исследование включает всесторонний анализ существующей литературы, методологий и проблем, связанных с применением этих датчиков. Авторы подчеркивают их эффективность в предоставлении данных в режиме реального времени о структурной целостности, что способствует профилактическому обслуживанию и повышению безопасности инфраструктурных объектов. В статье представлены примеры успешного применения волоконно-оптических датчиков, таких как мониторинг деформаций мостов, обнаружение утечек в трубопроводах и контроль трещин в зданиях. Рассмотрены текущие исследования, направленные на повышение точности датчиков, разработку новых конфигураций и методов анализа данных, а также интеграция с искусственным интеллектом и алгоритмами машинного обучения для улучшения обработки данных. Авторы обсуждают проблемы и ограничения, включая надежность датчиков, сложности их установки и экономическую эффективность, а также необходимость стандартизации протоколов развертывания и интерпретации данных. В заключении предлагаются рекомендации по будущим исследованиям и возможностям для улучшения технологии волоконно-оптических датчиков, включая расширение сотрудничества между академическими кругами, промышленностью и государственными учреждениями. Ключевые слова: волоконно-оптические датчики, высокоскоростные деформаций, бетонные конструкций, импульсное воздействие, оптический датчик деформации.

Improving the environmental safety and energy efficiency of water disinfection technologies is a key challenge in ecological engineering. This study proposes and experimentally validates a hybrid intelligent control system for a high – frequency ozonator based on a plasma – liquid process,...