Article
Chemistry, Analytical
Vit Novotny, Petr Sysel, Ales Prokes, Pavel Hanak, Karel Slavicek, Jiri Prinosil
Summary: This distributed long-range sensing system uses standard telecommunication single-mode optical fiber for distributed sensing of mechanical vibrations, enabling detection, localization, and classification of various vibration sources. The system components were designed, constructed, and tested in both laboratory and real deployment scenarios, with results presented in the paper.Additionally a two-fiber sensor unit with double sensing range was designed, constructed, and initial measurement results were presented.
Article
Chemistry, Analytical
Shahab Bakhtiari Gorajoobi, Ali Masoudi, Gilberto Brambilla
Summary: A Brillouin distributed acoustic sensor (DAS) based on optical time-domain refractometry has been developed, demonstrating a maximum detectable strain of 8.7 m epsilon and low signal fading. The sensor can accurately measure strain waves with frequencies up to 120 Hz at a sampling rate of 1.2 kHz and a spatial resolution of 4 m within a sensing range of 8.5 km. By using a modified inline Raman amplifier configuration with 80 ns Raman pump pulses, the signal-to-noise ratio is improved by 3.5 dB and the measurement accuracy is enhanced by a factor of 2.5 to 62 mu epsilon at the far-end of a 20 km fiber.
Article
Optics
Yining Pan, Tingkun Wen, Wei Ye
Summary: The study utilized distributed optical fiber sensing technology based on 0-OTDR, combined with a deep learning model to extract time-frequency sequence correlation from signals and spectrograms. A lightweight convolutional neural network architecture was designed, achieving a classification accuracy of 96.02%.
Article
Optics
Yuan Wang, Liang Chen, Xiaoyi Bao
Summary: The novel method proposed in this research uses a chirped pulse to extract Brillouin frequency shift changes in real time, allowing for static and dynamic strain measurement without the need for frequency sweeping. With high acquisition rate and spatial resolution, the system is immune to polarization fading issue.
Article
Optics
Jialin Jiang, Ziwen Deng, Zinan Wang
Summary: With the increasing demand for large-scale acoustic sensing in various fields, optical fiber-based distributed acoustic sensing (DAS) has experienced rapid development. The emergence of quasi-distributed acoustic sensing (QDAS) based on single-mode fiber with enhanced point array has provided a solution to improve signal-to-noise ratio and address interference-fading issues. However, like DAS, QDAS performance is limited by finite frequency domain resources, requiring additional resources for multiplexing sensing channels. Multiple-input multiple-output coding technology is an approach to achieve QDAS channel multiplexing with orthogonal probe waves in the same frequency band.
Review
Optics
Hongyu Yuan, Yu Wang, Rui Zhao, Xin Liu, Qing Bai, Hongjuan Zhang, Yan Gao, Baoquan Jin
Summary: A composite system incorporating MI, MZI, and Phi-OTDR structures was proposed in this paper to eliminate strong ambient noise affecting optical fiber vibration sensing system. The system successfully filtered out the frequency components of the noise, restored and located vibration signals up to 20 kHz, even in the presence of local ambient disturbances.
OPTICS AND LASERS IN ENGINEERING
(2021)
Article
Engineering, Electrical & Electronic
Mingyang Sun, Miao Yu, Peitong Lv, Asu Li, Haoran Wang, Xiaotong Zhang, Tiehu Fan, Tianyu Zhang
Summary: Real-time threat identification has been a focal point in the security field, with researchers developing the SE-WaveNet deep learning model to efficiently address risks in threat event identification. By introducing the SE structure of the attention mechanism, the SE-WaveNet adapts to matrix data with complete information. Experimental results show that SE-WaveNet outperforms other models in accuracy, model size reduction, and processing speed.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2021)
Article
Optics
Hao Li, Cunzheng Fan, Zhengxuan Shi, Baoqiang Yan, Junfeng Chen, Zhijun Yan, Deming Liu, Perry Shum, Qizhen Sun
Summary: This study proposes a spatio-temporal joint oversampling-downsampling technique to suppress noise in coherent fiber distributed acoustic sensing systems. By utilizing spatial oversampling and averaging downsampling, noise decreases with increasing downsampling coefficient, ensuring correct quantization of noise frequency. Experimental results show significant improvement in DAS system performance with this technique.
Article
Engineering, Electrical & Electronic
M. P. Lipus, S. Kranz, T. Reinsch, C. Cunow, J. Henninges, M. Reich
Summary: This paper presents a novel distributed shear stress sensor that allows for the derivation of fluid rheological parameters along a fiber-optic cable. Laboratory experiments have demonstrated that the sensor can distinguish differences of 1 mPa s dynamic viscosities in a low range.
SENSORS AND ACTUATORS A-PHYSICAL
(2022)
Article
Engineering, Electrical & Electronic
Xin Gui, Zhengying Li, Xuelei Fu, Huiyong Guo, Yiming Wang, Changjia Wang, Jiaqi Wang, Desheng Jiang
Summary: To achieve data-driven intelligence in engineering applications, distributed optical fiber sensor networks should have large capacity, long distance, dense distribution, fast response, and high signal-to-noise ratio (SNR). This research demonstrates the successful multiplexing and demodulation of thousands of fiber Bragg grating (FBG) sensors, by combining traditional optical reflectometry techniques with large-scale FBG arrays fabricated online. The fabrication, demodulation techniques, and applications of large-scale FBG arrays are reviewed, providing insights into key parameters such as multiplexing capacity, demodulation speed, spatial resolution, and SNR.
JOURNAL OF LIGHTWAVE TECHNOLOGY
(2023)
Article
Engineering, Electrical & Electronic
Hongyu Yuan, Rui Zhao, Yu Wang, Qing Bai, Hongjuan Zhang, Yan Gao, Baoquan Jin
Summary: This method successfully achieved long-distance detection of periodic vibration signals on a 90 km sensing fiber without additional optical amplification through global phase demodulation and autocorrelation processing.
IEEE SENSORS JOURNAL
(2021)
Article
Multidisciplinary Sciences
Jian Yang, Chen Wang, Jichao Yi, Yuankai Du, Maocheng Sun, Sheng Huang, Wenan Zhao, Shuai Qu, Jiasheng Ni, Xiangyang Xu, Ying Shang
Summary: This paper proposes a railway intrusion event classification and location scheme based on a distributed vibration sensing system. The 1DSE-ResNeXt+SVM method is used to improve accuracy and reliability. The method achieves high accuracy in field experiments, significantly enhancing railway safety.
Article
Optics
Xunzhou Xiao, Jun He, Bin DU, Xizhen Xu, Yiping Wang
Summary: This paper proposes a vectorial distributed acoustic sensing (vDAS) system based on Phi OTDR for distributed two-dimensional vector vibration measurements. The system utilizes an optical pulse compression algorithm and a Rayleigh-enhanced seven-core fiber to achieve high spatial resolution and suppress fading noise, enabling complete quantification of perturbations.
Article
Chemistry, Analytical
Aida Amantayeva, Nargiz Adilzhanova, Aizhan Issatayeva, Wilfried Blanc, Carlo Molardi, Daniele Tosi
Summary: A guidance system based on a network of fiber optic distributed sensors has been developed for epidural anesthesia, allowing real-time reconstruction of the epidural device silhouette and identification of bending patterns typical in epidural insertions to support the operator.
Article
Optics
Zhiyong Zhao, Li Shen, Yunli Dang, Chao Lu, Ming Tang
Summary: The novel fiber optic vibration sensor utilizes two counter-propagating interferometers to extend the sensing range significantly. The spatially separated structure of the interferometers allows for good correlation in the output waveforms, enabling direct determination of vibration location without the need for complicated data processing methods.
Article
Chemistry, Analytical
Christos Karapanagiotis, Aleksander Wosniok, Konstantin Hicke, Katerina Krebber
Summary: This study presents the first report on a machine-learning-assisted Brillouin optical frequency domain analysis (BOFDA) for time-efficient temperature measurements. A convolutional neural network (CNN)-based signal post-processing method is proposed to enhance temperature extraction and system performance, shortening measurement time by more than nine times.
Article
Instruments & Instrumentation
Rene Eisermann, Stephan Krenek, Georg Winzer, Steffen Rudtsch
Summary: Photonics sensors utilizing silicon-based ring resonators enable purely optical contact thermometry with high reproducibility and uniformity. Through laser-based spectroscopy and stable temperature control, precise characterization of the sensors was achieved, providing temperature stability within a wide range. The use of a hydrogen cyanide reference gas cell allowed for in-situ correction of the wavelength, while the analysis of resonance peaks demonstrated high optical quality and temperature sensitivity.
TM-TECHNISCHES MESSEN
(2021)
Article
Chemistry, Analytical
Rene Eisermann, Stephan Krenek, Tobias Habisreuther, Petra Ederer, Sigurd Simonsen, Helge Mathisen, Tino Elsmann, Frank Edler, Daniel Schmid, Adrian Lorenz, Age Andreas Falnes Olsen
Summary: This paper presents a hybrid optical temperature sensor based on S-FBG and thermal radiation signals, which is suitable for applications in harsh environments. The influence of thermal gradient and hotspot position on the sensor is analyzed, and the signal processing of the reflected S-FBG spectrum is investigated and enhanced. The sensor is calibrated using temperature-fixed points and shows high stability and robustness in field trials.
Article
Polymer Science
Xin Lu, Konstantin Hicke, Mathias Breithaupt, Christoph Strangfeld
Summary: This study presents a preliminary investigation on distributed humidity monitoring during the drying process of concrete using embedded polymer optical fiber (POF). Experimental results indicate that the signal received at 650 nm increases, while the fiber attenuation factor at 500 nm clearly increases, which is consistent with the measurement result of the electrical humidity sensors embedded in the concrete sample.
Article
Optics
Christos Karapanagiotis, Konstantin Hicke, Aleksander Wosniok, Katerina Krebber
Summary: In this paper, we report the first distributed relative humidity sensing in silica polyimide-coated optical fibers using Brillouin optical frequency domain analysis (BOFDA). The linear regression algorithm, a simple and well-interpretable machine learning and statistics method, is employed with the Brillouin frequency shifts and linewidths of the fiber's multipeak Brillouin spectrum as features. Machine learning concepts are utilized to estimate the model's uncertainties and select the most influential features to improve the regression algorithm's effectiveness. The model can also provide distributed temperature estimation simultaneously, addressing the cross-sensitivity effects.
Correction
Instruments & Instrumentation
Rene Eisermann, Stephan Krenek, Georg Winzer, Steffen Rudtsch
TM-TECHNISCHES MESSEN
(2022)
Article
Optics
Sabahat Shaheen, Konstantin Hicke
Summary: In this study, the geometric phase in the beat signal generated by coherent interference of two frequency-offset light beams was measured using a novel distributed optical fiber sensing setup. To the best of our knowledge, this is the first measurement of the mentioned geometric phase in a fiber optic medium with changing beam intensities. The experimental results of applying a 100-Hz sinusoidal stimulus to a polarization scrambler and a piezoelectric transducer inline to an optical fiber were presented. These results may enable the development of novel distributed fiber sensing techniques.
Article
Optics
Christos Karapanagiotis, Konstantin Hicke, Katerina Krebber
Summary: We present a novel approach combining machine learning and Brillouin frequency domain analysis (BOFDA) for simultaneous distributed temperature and strain sensing in a standard telecom optical fiber. By improving the signal-to-noise ratio and utilizing machine learning algorithms, the well-known temperature and strain cross-sensitivity problem is effectively addressed. The experimental results show that the proposed system achieves high accuracy in measuring temperature and strain, with errors of 2 degrees C and 45 mu epsilon, respectively, using Gaussian process regression (GPR) algorithm.
Article
Instruments & Instrumentation
Christos Karapanagiotis, Konstantin Hicke, Katerina Krebber
Summary: This paper introduces a machine learning assisted distributed fiber optic sensor (DFOS) for infrastructure monitoring. Artificial neural networks (ANNs) are used for signal processing to improve the performance of DFOS for strain and vibration sensing. Convolutional neural networks (CNNs) are employed to denoise the dynamic DFOS signal and enable longer sensing lengths. Machine learning algorithms are applied to solve the problem of cross-sensitivity in static DFOS. The presented machine learning assisted DFOS can enhance the monitoring of infrastructures.
TM-TECHNISCHES MESSEN
(2023)
Article
Multidisciplinary Sciences
Sabahat Shaheen, Konstantin Hicke, Katerina Krebber
Summary: A phase-sensitive optical time domain reflectometer based on coherent heterodyne detection of geometric phase in the beat signal of light is reported for the first time. The use of the geometric phase allows for strain measurement that is immune to polarisation diversity fading. The geometric phase is calculated using the amplitude of the beat signal and individual beam intensities without the need for phase unwrapping. This novel solution successfully measures strain without the limitations of polarisation mismatch fading and phase unwrapping errors.
SCIENTIFIC REPORTS
(2023)
Proceedings Paper
Engineering, Electrical & Electronic
Christos Karapanagiotis, Konstantin Hicke, Katerina Krebber
Summary: Machine learning has been widely used in the field of distributed fiber optic sensors for simultaneous measurement of temperature and humidity. Nonlinear machine learning algorithms have shown advantages over traditional linear regression, leading to potential new applications in civil and geotechnical engineering.
OPTICAL SENSING AND DETECTION VII
(2022)
Proceedings Paper
Materials Science, Multidisciplinary
Dorit Munzke, Eric Duffner, Rene Eisermann, Marcus Schukar, Andre Schoppa, Mariusz Szczepaniak, Joerg Strohhacker, Georg Mair
Summary: In this study, distributed fiber optic strain sensing was used to monitor a hybrid type IV composite fully wrapped pressure vessel, effectively detecting material fatigue and critical changes. Results showed that critical material changes could be detected 17,000 load cycles before material failure.
MATERIALS TODAY-PROCEEDINGS
(2021)
Proceedings Paper
Optics
K. Hicke, S. Chruscicki, K. Krebber
SEVENTH EUROPEAN WORKSHOP ON OPTICAL FIBRE SENSORS (EWOFS 2019)
(2019)