TY - JOUR A1 - Lu, Xin A1 - Chruscicki, Sebastian A1 - Schukar, Marcus A1 - Münzenberger, Sven A1 - Krebber, Katerina T1 - Application of Intensity-Based Coherent Optical Time Domain Reflectometry to Bridge Monitoring N2 - Although distributed fiber sensing techniques have been widely used in structural health monitoring, the measurement results of bridge monitoring, particularly under destructive testing, have rarely been reported. To the best of our knowledge, this paper is the first report of distributed vibration measurement results, which we obtained during a three-day destructive test on an abolished bridge. A coherent optical time domain reflectometry (COTDR) was used to acquire the vibration information while the bridge was being sawed. The obtained signal was analyzed in time and frequency domain. Some characteristics of the sawing-induced vibration were retrieved by the short-time Fourier transform; the vibration exhibited several high frequency components within the measured range up to 20 kHz and all the components appeared in the same time slot. Some unexpected signals were also detected. Thorough analysis showed that they are quite different from the sawing-induced vibration and are believed to originate from internal damage to the bridge (probably the occurrence of cracks). KW - Destructive testing KW - Structural health monitoring KW - Distributed fiber sensing KW - Distributed acoustic sensing PY - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-547451 VL - 22 IS - 9 SP - 3434 PB - MDPI AN - OPUS4-54745 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Zabihi, Mohammadmasoud A1 - Krebber, Katerina T1 - Approach for Faster Signal Processing in Փ-OTDR Systems Based on Directional Measurement of Fiber Slices Interaction N2 - In this study, a signal processing approach for heterodyne Փ-OTDR and C-OTDR systems that can obtain external perturbation and its frequency content in a faster way is proposed. We can detect vibrations with the same or better SNR using this processing approach, only with a single step and fast calculation. Fig. 12 shows the comparison of the normalized measurement time for the gamma matrix method and the conventional method throughout the three experiments. The speed of processing using a gamma matrix is ~35%–50% faster compared to a conventional method in high frequency test (PZT), low frequency test (walking) and street monitoring test. The processing speed in low frequency test is normally a bit lower than the similar high frequency one, since we must use higher number of time frames. Also, in street test we have higher speed because we can select wider gauges. KW - Փ-OTDR PY - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-560492 VL - 1 IS - 8 SP - 1837 EP - 1847 PB - Optica Publishing Group CY - Washington, DC AN - OPUS4-56049 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 - 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 - Distributed fiber sensing KW - Acoustic sensing KW - Response characterization PY - 2022 AN - OPUS4-56099 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Karapanagiotis, Christos A1 - Hicke, Konstantin A1 - Wosniok, Aleksander A1 - Krebber, Katerina T1 - Distributed humidity fiber-optic sensor based on BOFDA using a simple machine learning approach N2 - We report, to our knowledge for the first time, on distributed relative humidity sensing in silica polyimide-coated optical fibers using Brillouin optical frequency domain analysis (BOFDA). Linear regression, which is a simple and well-interpretable algorithm in machine learning and statistics, is utilized. The algorithm is trained using as features the Brillouin frequency shifts and linewidths of the fiber’s multipeak Brillouin spectrum. To assess and improve the effectiveness of the regression algorithm, we make use of machine learning concepts to estimate the model’s uncertainties and select the features that contribute most to the model’s performance. In addition to relative humidity, the model is also able to simultaneously provide distributed temperature information addressing the well-known cross-sensitivity effects. KW - Fiber optics sensors KW - Machine learning KW - Brillouin distributed sensing KW - Humidity sensing KW - Simultaneous temperature and humidity sensing PY - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-546294 VL - 30 IS - 8 SP - 12484 EP - 12494 PB - OPTICA AN - OPUS4-54629 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Königsbauer, Korbinian A1 - Nöther, N. A1 - Schaller, M. B. A1 - Wosniok, Aleksander A1 - Krebber, Katerina T1 - Distributed POF sensors for structural health monitoring in civil construction applications N2 - In this paper, a cost-efficient distributed fiber optic measurement system based on Rayleigh scattering is presented. The distributed digital incoherent optical frequency domain reflectometry (I-OFDR) method is developed for detection of significantly large strain in the range from 3 % up to 10 % as required by end users. For this purpose, a vector network analyzer used in the I-OFDR is replaced by a compact and cost-effective digital data acquisition system. This digital emitting/receiving unit enables the recording of the complex transfer function carrying information about the local deformations along the entire sensing fiber. T2 - POF 2022 The 30th International Conference on Plastic Optical Fibers CY - Bilbao, Spain DA - 26.09.2022 KW - I-OFDR KW - PF-POF KW - Structural health monitoring KW - Rayleigh backscatter measurement KW - Strain detection PY - 2022 VL - 2022 SP - 152 EP - 155 AN - OPUS4-56060 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Zabihi, Mohammadmasoud A1 - Krebber, Katerina T1 - Laser source frequency drift compensation in Φ-OTDR systems using multiple probe frequencies N2 - In this study, an approach for mitigation of LSFD in Φ-OTDR systems was proposed. By using one probe pulse as a reference in a system with two or more probe frequencies, we can remove unwanted low frequency noise that is originally caused by the laser source. Although LSFD is problematic issue, it is not the only source of low frequency noise. Change in temperature, humidity, physical surroundings, environment, etc., can result in such noises. The proposed method; however, is expected to highly suppresses all of these effects, regardless of their source, either in the time or frequency domain. For comparing reference and probe signals, there are sophisticated methods, rather than normal differentiation, available for use. Some of these methods have a close relationship with CPD methods and can further enhance the results. These methods can be further discussed in an independent research or future work. The proposed method is very helpful for increasing accuracy in passive and active seismic monitoring, reservoir monitoring, underwater monitoring, etc. It also helps using relatively simpler laser sources and make the whole system price-efficient, as well as processing data without lengthy compensation algorithms. KW - Frequency Drift KW - Փ-OTDR KW - LSFD PY - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-560517 SN - 1094-4087 VL - 30 IS - 11 SP - 19990 EP - 19998 PB - Optica CY - Washington, DC AN - OPUS4-56051 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 - JOUR A1 - Lu, Xin A1 - Krebber, Katerina T1 - Phase error analysis and unwrapping error suppression in phase-sensitive optical time domain reflectometry N2 - Phase-sensitive optical time domain reflectometry becomes an effective tool to realize distributed sensing, and the optical phase of the received light is usually used to quantify the strain for both dynamic and static measurement. The analysis on the overall phase error has been improved by considering the proportionality of the detection noise to the local optical power. The estimation accuracy is greatly improved by using the proposed theory, the probability density of the estimation accuracy over 99% is > 0.6, ∼39 times larger than the previously reported method. The phase unwrapping may malfunction due to the noisy signal, causing large phase errors. Point break detection algorithms are used to locate the incorrect phase unwrapping points, so the temporal evolution of the phase retrieved at each position can be divided into several sections with different offset. The phase unwrapping error is then suppressed by removing the offset. KW - Phase unwrapping KW - Distributed fiber sensing KW - Acoustic sensing PY - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-543919 VL - 30 IS - 5 SP - 6934 EP - 6948 PB - Optica Publishing Group AN - OPUS4-54391 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 U6 - 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 -