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Application of machine learning in optical fiber sensors
In recent years, with the increasing demand for intelligent society, intelligent photonics has
developed rapidly. Machine learning (ML), as a subset of artificial intelligence (AI), has …
developed rapidly. Machine learning (ML), as a subset of artificial intelligence (AI), has …
[HTML][HTML] Activation function dynamic averaging as a technique for nonlinear 2D data denoising in distributed acoustic sensors
This work studies the application of low-cost noise reduction algorithms for the data
processing of distributed acoustic sensors (DAS). It presents an improvement of the …
processing of distributed acoustic sensors (DAS). It presents an improvement of the …
Emerging technologies for Fiber-Optic Based Sensors in Biomedical Domain: A Review and Recent Developments
RS Bujugundla, HS Pradhan - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Fiber-optic sensor (FOS) technology, a proximate of optoelectronics and fiber-optic
communications, has profound ability to replace the existent biomedical sensors …
communications, has profound ability to replace the existent biomedical sensors …
Distributed fiber optic sensors for structural health monitoring of composite pressure vessels
C Karapanagiotis, M Schukar, K Krebber - tm-Technisches Messen, 2024 - degruyter.com
In this paper, we present a comprehensive overview of our research in the field of distributed
fiber optic sensors for structural health monitoring of hydrogen composite pressure vessels …
fiber optic sensors for structural health monitoring of hydrogen composite pressure vessels …
Machine learning-augmented multi-arrayed fiber bragg grating sensors for enhanced structural health monitoring by discriminating strain and temperature variations
Fiber optic sensors (FOS) in long-term structural health monitoring (SHM) have drawn
significant attention due to their pivotal role in detecting defects and measuring structural …
significant attention due to their pivotal role in detecting defects and measuring structural …
Achieving precise multiparameter measurements with distributed optical fiber sensor using wavelength diversity and deep neural networks
The development of advanced distributed optical fiber sensing systems that are capable of
performing accurate and spatially resolved multiparameter measurements is of great interest …
performing accurate and spatially resolved multiparameter measurements is of great interest …
[HTML][HTML] The Impact of Liquids and Saturated Salt Solutions on Polymer-Coated Fiber Optic Sensors for Distributed Strain and Temperature Measurement
M Weisbrich, D Messerer, F Holzer, U Trommler… - Sensors, 2024 - mdpi.com
The application of distributed fiber optic strain and temperature measurement can be utilized
to address a multitude of measurement tasks across a diverse range of fields, particularly in …
to address a multitude of measurement tasks across a diverse range of fields, particularly in …
[HTML][HTML] An Image Processing-Based Correlation Method for Improving the Characteristics of Brillouin Frequency Shift Extraction in Distributed Fiber Optic Sensors
Y Konstantinov, A Krivosheev, F Barkov - Algorithms, 2024 - mdpi.com
This paper demonstrates how the processing of Brillouin gain spectra (BGS) by two-
dimensional correlation methods improves the accuracy of Brillouin frequency shift (BFS) …
dimensional correlation methods improves the accuracy of Brillouin frequency shift (BFS) …
[HTML][HTML] Thermal compensation of monolithic distributed fibre optic sensors: From the lab to the field
Distributed fibre optic sensing (DFOS) is gaining popularity as a diagnostic solution for short-
term non-destructive testing (NDT) and long-term structural health monitoring (SHM) …
term non-destructive testing (NDT) and long-term structural health monitoring (SHM) …
Temporal Forecasting of Distributed Temperature Sensing in a Thermal Hydraulic System with Machine Learning and Statistical Models
We benchmark performance of long-short term memory (LSTM) network ML model and
Autoregressive Integrated Moving Average (ARIMA) statistical model in temporal forecasting …
Autoregressive Integrated Moving Average (ARIMA) statistical model in temporal forecasting …