TY - CONF A1 - Wosniok, Aleksander A1 - Karapanagiotis, Christos T1 - Brillouin optical frequency-domain analysis for structural health monitoring N2 - We present our achievements in the development of distributed fiber optic sensing systems based on Brillouin optical frequency-domain analysis for structural health monitoring. The focus of the applications is on the gapless monitoring of geotechnical structures, large area infrastructures and electrical grids. The work includes the latest use of machine learning algorithms to reduce measurement time by coexistent increasing the measurement accuracy. T2 - 4th Workshop on Optomechanics and Brillouin Scattering CY - Erlangen, Germany DA - 14.06.2022 KW - Distributed sensing KW - BOFDA KW - Optical fiber sensor KW - Brillouin distributed fiber sensor PY - 2022 AN - OPUS4-55173 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Karapanagiotis, Christos T1 - Evaluation of the generalization performance of a CNN-assisted BOFDA system N2 - Brillouin Optical Frequency Domain Analysis (BOFDA) is a powerful and well-established method for static distributed sensing of temperature and strain. Recently, we demonstrated a BOFDA system based on convolutional neural network which shortens the measurement time considerably. In this paper, we apply leave-one-out cross validation to evaluate the generalization performance and provide an unbiased and reliable machine learning model for a time-efficient BOFDA system. T2 - 21. ITG/GMA Fachtagung Sensoren und Messsysteme 2022 CY - Nuremberg, Germany DA - 10.05.2022 KW - Fiber optics sensors KW - BOFDA KW - Brillouin distributed sensing KW - Machine learning PY - 2022 UR - https://www.ama-science.org/direct/tagungsband-sensoren-und-messsysteme-2022 SN - 978-3-8007-5835-7 SP - 289 EP - 292 PB - VDE VERLAG GMBH AN - OPUS4-55183 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Karapanagiotis, Christos A1 - Hicke, Konstantin A1 - Krebber, Katerina T1 - Temperature and humidity discrimination in Brillouin distributed fiber optic sensing using machine learning algorithms N2 - In the last few years, the use of machine learning has emerged in the field of distributed fiber optic sensors as a promising approach to enhance their performance and provide new capabilities. In this study, we use machine learning for simultaneous measurements of temperature and humidity in polyimide (PI)-coated optical fibers based on Brillouin Brillouin optical frequency domain analysis (BOFDA). Different non-linear machine learning algorithms are employed, namely polynomial regression, decision trees and artificial neural networks (ANNs), and their discrimination performance is benchmarked against that of the conventional linear regression. The performance is evaluated using leave-one-out cross-validation to ensure that the models are reliable and able to generalize well on new data. We show that nonlinear machine learning algorithms outperform the conventional linear regression and thus could pave the way towards simultaneous cost-effective temperature and humidity distributed sensing, which has the potential to find attractive new applications in the field of civil and geotechnical engineering, from structural health monitoring of dikes and bridges to subsea cables and long pipelines corrosion detection. T2 - SPIE Photonics Europe 2022 CY - Strasbourg, France DA - 03.04.2022 KW - Distributed Brillouin sensing KW - Machine learning KW - Artificial neural networks KW - Simultaneous temperature and humidity sensing KW - BOFDA PY - 2022 DO - https://doi.org/10.1117/12.2620985 VL - 12139 SP - 1 EP - 7 PB - SPIE AN - OPUS4-54861 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Karapanagiotis, Christos T1 - Evaluation of the generalization performance of a CNN-assisted BOFDA system N2 - Brillouin Optical Frequency Domain Analysis (BOFDA) is a powerful and well-established method for static distributed sensing of temperature and strain. Recently, we demonstrated a BOFDA system based on convolutional neural network which shortens the measurement time considerably. In this paper, we apply leave-one-out cross validation to evaluate the generalization performance and provide an unbiased and reliable machine learning model for a time-efficient BOFDA system. T2 - 21. ITG/GMA Fachtagung Sensoren und Messsysteme 2022 CY - Nürnberg, Germany DA - 10.05.2022 KW - Fiber optics sensors KW - BOFDA KW - Convolutional neural networks KW - Machine learning KW - Temperature sensing PY - 2022 AN - OPUS4-54862 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Hicke, Konstantin A1 - Wosniok, Aleksander A1 - Krebber, Katerina T1 - Distributed fiber optic radiation sensors for nuclear applications N2 - Advantages and underlying principles of distributed fiber optic radiation sensing are discussed. Differences with regard to dose measurement range and resolution between glass optical fiber based sensing and polymer optical fiber based sensing are outlined. T2 - DGZfP SMIRT26 Laborbesuch (BAM) CY - Berlin, Germany DA - 10.07.2022 KW - Distributed fiber optic sensing KW - Fiber optic radiation monitoring KW - Distributed fiber optic radiation sensing PY - 2022 AN - OPUS4-55264 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Lu, Xin A1 - Schukar, Marcus A1 - Krebber, Katerina T1 - Characterizing vibration response of fiber cables for distributed acoustic sensing N2 - The vibration responses of two fiber cables are characterized up to 16 kHz and compared with a standard tight-buffered 900 um fiber. The response of the cables is suppressed due to the cable protection T2 - 27th International Conference on Optical Fiber Sensors (OFS-27) CY - Alexandria, VA, USA DA - 29.08.2022 KW - Response characterization KW - Distributed fiber sensing KW - Acoustic sensing PY - 2022 SP - 1 EP - 4 PB - Optica CY - Washington D.C., USA AN - OPUS4-56096 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Lu, Xin A1 - Schukar, Marcus A1 - Weege, S. A1 - Roske, T. A1 - Krebber, Katerina T1 - Leakage detection at a borehole simulator using distributed acoustic sensing N2 - A distributed acoustic sensing system is used to detect the leakage in a borehole simulator by measuring the leakage induced vibration. The leakage location can be clearly determined by frequency spectrum analysis. T2 - 27th International Conference on Optical Fiber Sensors (OFS-27) CY - Alexandria, VA, USA DA - 29.08.2022 KW - Leakage detection KW - Structural health monitoring KW - Distributed fiber sensing KW - Distributed acoustic sensing PY - 2022 SP - 1 EP - 4 PB - Optica CY - Washington D.C., USA AN - OPUS4-56097 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Lu, Xin A1 - Schukar, Marcus A1 - Weege, S. A1 - Roske, T. A1 - Krebber, Katerina T1 - Leakage detection at a borehole simulator using distributed acoustic sensing N2 - A distributed acoustic sensing system is used to detect the leakage in a borehole simulator by measuring the leakage induced vibration. The leakage location can be clearly determined by frequency spectrum analysis. T2 - 27th International Conference on Optical Fiber Sensors (OFS-27) CY - Alexandria, VA, USA DA - 29.08.2022 KW - Structural health monitoring KW - Distributed fiber sensing KW - Distributed acoustic sensing KW - Leakage detection PY - 2022 AN - OPUS4-56098 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Wosniok, Aleksander A1 - Krebber, Katerina T1 - Achievements and challenges of distributed polymer optical fiber sensors @BAM N2 - Monitoring of construction projects plays increasingly important role in the implementation of growing needs and requirements, especially in geologically difficult areas. This particularly concerns tunnelling and special civil engineering projects. The use of fiber optic sensors for structural health monitoring provides significant economic advantages regarding lower life-cycle costs of the civil infrastructure. We present our achievements in the development of distributed polymer optical fiber sensors based on Rayleigh and Brillouin scattering for early damage detection. T2 - POF Conference CY - Bilbao, Spain DA - 26.09.2022 KW - Distributed POF sensor KW - OTDR KW - OFDR KW - Smart geosynthetics PY - 2022 AN - OPUS4-56031 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Shaheen, Sabahat A1 - Hicke, Konstantin T1 - Measurement of Geometric Phase using a φ-OTDR setup N2 - Geometric phase showing sensitivity to changes in polarisation state and intensity of backscattered light is measured using a novel φ-OTDR setup based on coherent heterodyne detection. Principle is demonstrated using a polarisation scrambler inline a fiber-under-test. T2 - Optical Fiber Sensors 2022 CY - Alexandria, Virginia, United States DA - 29.08.2022 KW - Coherent Heterodyne KW - Geometric Phase KW - Distributed Fiber Optic Sensor PY - 2022 SN - 978-1-957171-14-2 SP - W4.72 AN - OPUS4-56116 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -