TY - CONF A1 - Stajanca, Pavol A1 - Topolniak, Ievgeniia A1 - Pötschke, Samuel A1 - Krebber, Katerina ED - Kalli, K. ED - Mendez, A. ED - Bunge, C.-A. T1 - Solution doping of commercial plastic optical fibers N2 - Solution doping of off-the-shelf plastic optical fibers (POFs) represents rather simple and cheap way for preparing custom cladding-doped POFs (CD-POFs) with short to medium lengths. CD-POFs are especially attractive for environmental sensing applications, but might be of interest for illumination task as well. In this work, the proposed doping technique is tested with three different commercial low-cost polymethyl methacrylate (PMMA) POFs; Eska CK-40 and Eska GK-40 from Mitsubishi Rayon and Raytela PGU-FB1000 from Toray. The aim of the work is to aid the selection of the most suitable fiber yielding highest optical quality of prepared CD-POFs. Firstly, the optimal doping times are determined for the individual fiber types using short fiber samples. Secondly, longer 10 m CD-POFs are prepared from all tested fibersusing the optimized doping procedure. Finally, attenuation of pristine POFs and prepared CD-POFs is measured using optical time domain reflectometry in order to characterize the impacts of the doping on fiber optical properties. In addition, the importance of post-doping drying procedure for CD-POF optical performance is investigated as well. The results suggest that, although doping of all tested fibers is generally feasible, Eska CK-40 is the most suitable candidate with regard to the Doping efficiency and fiber post-doping performance. T2 - SPIE Photonics Europe 2018 CY - Strasbourg, France DA - 22.04.2018 KW - Plastic optical fibers KW - Solution doping KW - Polzmethyl methacrylate KW - PMMA KW - Rhodamine B KW - Fluorescent optical fibers KW - Cladding-doped fibers PY - 2018 DO - https://doi.org/10.1117/12.2315619 SN - 0277-786X VL - 10681 SP - 106810O-1 EP - 106810O-7 AN - OPUS4-44907 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Kapa, Thomas A1 - Schreier, Andy A1 - Krebber, Katerina T1 - 63 km BOFDA for temperature and strain monitoring N2 - We demonstrate (and are the first to do so) 63 km Brillouin Optical Frequency-Domain Analysis (BOFDA) for temperature and strain monitoring using a 100 km fiber loop. The use of BOFDA for long-range applications can be considered a novel approach, as previous investigations focused on the utilization of Brillouin Optical Time-Domain Reflectometry and Analysis (BOTDR and BOTDA, respectively). At 51.7 km, a 100 m hotspot (37 °C) was detected without using distributed Raman amplification or image processing. KW - Distributed sensing KW - Stimulated Brillouin scattering KW - Fiber optics sensors PY - 2018 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-449679 DO - https://doi.org/10.3390/s18051600 SN - 1424-8220 VL - 18 IS - 5 SP - 1600, 1 EP - 9 PB - MDPI CY - Basel, Switzerland AN - OPUS4-44967 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Liehr, Sascha A1 - Münzenberger, Sven A1 - Krebber, Katerina T1 - Wavelength-scanning coherent OTDR for dynamic high strain resolution sensing N2 - Distributed vibration sensing in optical fibers opened entirely new opportunities and penetrated various sectors from security to seismic monitoring. Here, we demonstrate a most simple and robust approach for dynamic strain measurement using wavelength-scanning coherent optical time domain reflectometry (C-OTDR). Our method is based on laser current modulation and Rayleigh backscatter shift correlation. As opposed to common single-wavelength phase demodulation techniques, also the algebraic sign of the strain change is retrieved. This is crucial for the intended applications in structural health monitoring and modal analysis. A linear strain response down to 47.5 pε and strain noise of 100 pε/√Hz is demonstrated for repetition rates in the kHz range. A field application of a vibrating bridge is presented. Our approach provides a cost-effective high-resolution method for structural vibration analysis and geophysical applications. KW - Fiber optics sensors KW - Optical time domain reflectometry KW - Rayleigh Scattering KW - Distributed acoustic sensing KW - Distributed strain sensing PY - 2018 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-448069 DO - https://doi.org/10.1364/OE.26.010573 SN - 1094-4087 VL - 26 IS - 8 SP - 10573 EP - 10588 PB - Optical Society of America AN - OPUS4-44806 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Wosniok, Aleksander A1 - Krebber, Katerina T1 - Smart geosynthetics for structural health monitoring applications N2 - Responding to a growing need for intelligent monitoring of critical geotechnical and civil infrastructures, new multifunctional geotextiles and geogrids with integrated optical fibers were developed and investigated within several research projects. Such smart two-dimensional geosynthetics intercorporating optical fibers as distributed sensors provide solutions both for soil reinforcement, erosion control, drainage or environmental protection and for cost-effective monitoring of critical mechanical deformations and temperature distribution in geotechnical and masonry structures at the same time. The integrated fiber optic sensors provide online information about the condition of the monitored structure and about the occurrence and localization of any damage or degradation for the purpose of preventing a total collapse. T2 - The Fiber Society's Spring 2017 Conference CY - Institut für Textiltechnik der RWTH Aachen, Germany DA - 17.05.2017 KW - Smart geosynthetics KW - Sensor-based geotextiles KW - Fiber optic sensor KW - POF sensor KW - Distributed sensing PY - 2017 SP - 43 AN - OPUS4-42560 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Stajanca, Pavol A1 - Krebber, Katerina ED - Nogueira, R. ED - Rocha, A. M. T1 - Polymer optical fibers as radiation sensors? N2 - Application importance of ionizing radiation has been growing steadily over the last decades. Extensive utilization of ionizing radiation generates demand for development of suitable monitoring techniques. Radiation monitoring systems based on optical fibers offer several key advantages such as small footprint, possibility of remote and real-time measurement as well as electromagnetic immunity. In this contribution, we investigate radiation-induced attenuation (RIA)-based sensing with perfluorinated polymer optical fibers (PF-POFs). The RIA response of two commercial PF-POFs is assessed in a low dose region and performance and limitations of the system are discussed. The concept represents a potential high-sensitivity, low-cost and easy-to-use on-line radiation monitoring system with distributed detection capability T2 - 26thth International Conference on Plastic Optical Fibres (POF 2017) CY - Aveiro, Portugal DA - 13.09.2017 KW - Perfluorinated polymer optical fibers KW - Gamma radiation KW - Radiation monitoring KW - Optical fiber sensor PY - 2017 SN - 978-989-97345-2-4 SP - Paper 5, 1 EP - 4 AN - OPUS4-42318 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Stajanca, Pavol A1 - Krebber, Katerina ED - Nogueira, R. ED - Rocha, A. M. T1 - Post-fabrication cladding doping of commercial PMMA polymer optical fiber N2 - Possibility of post-fabrication doping of commercial PMMA fibers using well-known solution doping technique is presented. The cladding of 1 mm PMMA fiber is doped with Rhodamine B with the help of methanol-mediated diffusion of the dye molecules into the fiber material. Doping of the fiber core was not possible even at extended doping times. The proposed method represents rather simple and cheap way for preparing custom cladding-doped POFs with high flexibility of dopant choice and fiber length. Produced cladding-doped fibers have potential for various sensing or lighting applications. T2 - 26th International Conference on Plastic Optical Fibres (POF 2017) CY - Aveiro, Portugal DA - 13.09.2017 KW - Polymer optical fibers KW - Fluorescent dyes KW - Solution doping KW - Polymethyl methacrylate PY - 2017 SN - 978-989-97345-2-4 SP - Paper 14, 1 EP - 4 AN - OPUS4-42319 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Schreier, Andy A1 - Liehr, Sascha A1 - Wosniok, Aleksander A1 - Krebber, Katerina T1 - Investigation on the influence of humidity on stimulated Brillouin backscattering in perfluorinated polymer optical fibers N2 - In this paper perfluorinated graded-index polymer optical fibers are characterized with respect to the influence of relative humidity changes on spectral transmission absorption and Rayleigh backscattering. The hygroscopic and thermal expansion coefficient of the fiber are determined to be CHE = (7.4 +/- 0.1) 10^-6 %r.h.^-1 and CTE = (22.7 +/- 0.3) 10^-6 K^-1, respectively. The influence of humidity on the Brillouin backscattering power and linewidth are presented for the first time to our knowledge. The Brillouin backscattering power at a pump wavelength of 1319 nm is affected by temperature and humidity. The Brillouin linewidth is observed to be a function of temperature but not of humidity. The strain coefficient of the BFS is determined to be CS = (146.5 +/- 0.9) MHz/% for a wavelength of 1319 nm within a strain range from 0.1 % to 1.5 %. The obtained results demonstrate that the humidity-induced Brillouin frequency shift is predominantly caused by the swelling of the fiber over-cladding that leads to fiber straining. KW - Brillouin KW - Polymer optical fibre KW - Humidity PY - 2018 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-465932 DO - https://doi.org/10.3390/s18113952 SN - 1424-8220 VL - 18 IS - 11 SP - 3952, 1 EP - 12 PB - MDPI CY - Basel, Switzerland AN - OPUS4-46593 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Wosniok, Aleksander A1 - Krebber, Katerina A1 - Glötzl, R. ED - Boller, C. T1 - Temperature-corrected determination of mechanical deformations in geotechnical structures using Brillouin-based fiber optic sensors N2 - Structural Health Monitoring based on distributed Brillouin measuring techniques has been playing bigger and bigger role for applications in large-scale critical structures over the last decade. The Brillouin sensing techniques make use of low-loss single-mode optical fibers as distributed sensors allowing compound strain and temperature profile discrimination along the measured section even over several tens of kilometers. Thereby, the measured Brillouin frequency shift (BFS) features much stronger dependence on the longitudinal strain in the sensor fiber than on the temperature distribution along the fiber optic sensor. By detection of slight structural changes in monitored civil structures, such as dams, pipelines and tunnels, the influence of temperature on the measured BFS cannot be neglected. In simple cases of fiber optic sensors embedded deeply enough into earth structures no significant temperature gradients caused by weather conditions such as sunrays could be observed. The temperature contributes here only to the signal offset and the local mechanical deformations arisen due to soil displacement can be read directly from the distribution of the BFS. Also special cable solutions for separate determination of temperature and strain have been tested by us under field conditions. The use of two separate optical fibers for strain and temperature detection limits the spatial resolution and measurement accuracy in the determination of both physical quantities. In search of the optimal sensory solution for monitoring of mechanical deformations taking into account the temperature component in the measured signal the use of so called nonzero dispersion-shifted fibers has been investigated in several laboratory tests. Due to different doping concentration in the core new resonance acoustic modes can propagate in such optical fibers which results in multipeak structure in the Brillouin gain spectrum (BGS). The appearance of more than one resonance peak in the BGS offers the possibility to realize simultaneous measurement of longitudinal strain and temperature by analysis of applicable BFSs as function of both physical quantities using only one low cost optical fiber. T2 - EWSHM'12 - 6th European workshop on structural health monitoring 2012 CY - Dresden, Germany DA - 03.07.2012 KW - Structural health monitoring KW - Brillouin scattering KW - Distributed sensor PY - 2012 SN - 978-3-940283-41-2 VL - 1 SP - 417 EP - 422 CY - Berlin AN - OPUS4-26311 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Karapanagiotis, Christos A1 - Hicke, Konstantin A1 - Krebber, Katerina T1 - Eine Sammlung durch Maschinelles Lernen unterstützter Verteilter Faseroptischer Sensoren für Infrastrukturmonitoring T1 - A collection of machine learning assisted distributed fiber optic sensors for infrastructure monitoring N2 - In this paper, we present a collection of machine learning assisted distributed fiber optic sensors (DFOS) for applications in the field of infrastructure monitoring. We employ advanced signal processing based on artificial neural networks (ANNs) to enhance the performance of the dynamic DFOS for strain and vibration sensing. Specifically, ANNs in comparison to conventional and computationally expensive correlation and linearization algorithms, deliver lower strain errors and speed up the signal processing allowing real time strain monitoring. Furthermore, convolutional neural networks (CNNs) are used to denoise the dynamic DFOS signal and enable useable sensing lengths of up to 100 km. Applications of the machine learning assisted dynamic DFOS in road traffic and railway infrastructure monitoring are demonstrated. In the field of static DFOS, machine learning is applied to the well-known Brillouin optical frequency domain analysis (BOFDA) system. Specifically, CNN are shown to be very tolerant against noisy spectra and contribute towards significantly shorter measurement times. Furthermore, different machine learning algorithms (linear and polynomial regression, decision trees, ANNs) are applied to solve the well-known problem of cross-sensitivity in cases when temperature and humidity are measured simultaneously. The presented machine learning assisted DFOS can potentially contribute towards enhanced, cost effective and reliable monitoring of infrastructures. N2 - In diesem Beitrag stellen wir eine Sammlung von verteilten faseroptischen Sensoren (DFOS) vor, die mit Hilfe von Maschinellem Lernen arbeiten und für Anwendungen im Bereich der Infrastrukturüberwachung geeignet sind. Wir setzen hierbei fortschrittliche Signalverarbeitung auf der Grundlage Künstlicher Neuronaler Netze ein, um die Leistungsfähigkeit dynamischer DFOS für die Messung von Dehnungen und Vibrationen zu verbessern. Insbesondere Künstliche Neuronale Netze (ANNs) liefern im Vergleich zu konventionellen und rechenintensiven Korrelations- und Linearisierungsalgorithmen geringere Dehnungsfehler und beschleunigen die Signalverarbeitung, so dass eine Dehnungsüberwachung in Echtzeit möglich ist. Darüber hinaus wenden wir Convolutional Neural Networks (CNNs) an, um dynamische DFOS-Signale zu entrauschen und damit nutzbare Messlängen von bis zu 100 km zu ermöglichen. Es werden Anwendungsbeispiele dieser durch Maschinelles Lernen unterstützten dynamischen DFOS in den Bereichen des Straßenverkehrsmonitorings und der Zug- und Gleisüberwachung aufgezeigt. Im Bereich der statischen DFOS wird Maschinelles Lernen auf das Verfahren der Optischen Brillouin-Frequenzbereichsanalyse (BOFDA) angewendet. Insbesondere CNN erweisen sich hier als sehr robust gegenüber verrauschten Spektren und tragen zu deutlich kürzeren Messzeiten bei. Darüber hinaus werden verschiedene Algorithmen des maschinellen Lernens (lineare und polynome Regression, Entscheidungsbäume, ANNs) angewandt, um das bekannte Problem der Querempfindlichkeit bei DFOS in den Fällen zu lösen, in denen Temperatur und Feuchtigkeit gleichzeitig gemessen werden sollen. Die hier vorgestellten, durch Maschinelles Lernen unterstützten, DFOS können zu einer verbesserten, kostengünstigen und zuverlässigen Überwachung von Infrastrukturen beitragen. KW - Artificial neural networks KW - Brillouin sensing KW - Distributed acoustic sensing KW - Fibre optic sensors KW - Infrastructure monitoring PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-569044 DO - https://doi.org/10.1515/teme-2022-0098 SN - 0171-8096 SP - 1 EP - 19 PB - De Gruyter AN - OPUS4-56904 LA - mul AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Karapanagiotis, Christos A1 - Krebber, Katerina T1 - Machine Learning Approaches in Brillouin Distributed Fiber Optic Sensors N2 - This paper presents reported machine learning approaches in the field of Brillouin distributed fiber optic sensors (DFOSs). The increasing popularity of Brillouin DFOSs stems from their capability to continuously monitor temperature and strain along kilometer-long optical fibers, rendering them attractive for industrial applications, such as the structural health monitoring of large civil infrastructures and pipelines. In recent years, machine learning has been integrated into the Brillouin DFOS signal processing, resulting in fast and enhanced temperature, strain, and humidity measurements without increasing the system’s cost. Machine learning has also contributed to enhanced spatial resolution in Brillouin optical time domain analysis (BOTDA) systems and shorter measurement times in Brillouin optical frequency domain analysis (BOFDA) systems. This paper provides an overview of the applied machine learning methodologies in Brillouin DFOSs, as well as future perspectives in this area. KW - Distributed fiber optic sensors KW - BOTDA KW - BOFDA KW - Machine learning KW - Strain and temperature measurements KW - Artificial neural networks PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-580145 DO - https://doi.org/10.3390/s23136187 VL - 23 IS - 13 SP - 1 EP - 26 PB - MDPI AN - OPUS4-58014 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -