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We present a technique for distributed temperature gradient sensing in real-time along an optical fiber utilizing simple amplitude-based direct-detection coherent optical time domain reflectometry (C-OTDR) and a special sensing fiber. Our technique enables us to determine phase changes or low-frequency variations of the C-OTDR signal stemming from temperature variations. The distinct feature of the used sensing fiber is its structuring with equidistant strongly scattering dots. Consecutive pairs of these scatterers form the dominant local interferometers, effectively overwriting the otherwise highly nonlinear transfer function of common optical fiber. This enables a quasi-phase-resolved evaluation of perturbation responses originating from temperature changes at sensor positions between the scatterers. Using our method, we show the measurement of a nonlinear temperature transient from a heating process with a maximum temperature gradient of 0.8 °C over 20 s and a total temperature increase of 28.4 °C. This method requires almost no post-processing and can be used for simultaneous distributed vibration sensing (DVS) and quantification of local temperature gradients in a single fiber, e.g., for the use in condition monitoring of infrastructure or industrial installations.
We present a technique for distributed temperature gradient sensing in real-time along an optical fiber utilizing simple amplitude-based direct-detection coherent optical time domain reflectometry (C-OTDR) and a special sensing fiber. Our technique enables us to determine phase changes or low-frequency variations of the C-OTDR signal stemming from temperature variations. The distinct feature of the used sensing fiber is its structuring with equidistant strongly scattering dots. Consecutive pairs of these scatterers form the dominant local interferometers, effectively overwriting the otherwise highly nonlinear transfer function of common optical fiber. This enables a quasi-phase-resolved evaluation of perturbation responses originating from temperature changes at sensor positions between the scatterers. Using our method, we show the measurement of a nonlinear temperature transient from a heating process with a maximum temperature gradient of 0.8 °C over 20 s and a total temperature increase of 28.4 °C. This method requires almost no post-processing and can be used for simultaneous distributed vibration sensing (DVS) and quantification of local temperature gradients in a single fiber, e.g., for the use in condition monitoring of infrastructure or industrial installations.
Geometric phase measured per beat period in a ϕ-OTDR based on coherent heterodyne detection is used to measure strain. Proposed method is robust to polarisation mismatch fading as a polarisation mismatch between interfering beams is not a hindrance to the measurement of the geometric phase. The Geometric phase is a function of the intensities of the interfering beams as well as the envelope of the beat signal. Its calculation does not require phase unwrapping and accordingly does not suffer the phase unwrapping errors. It is required to be equated with the traditionally measured phase by applying a scaling factor. The spatial resolution of the measured strain is reduced as it is calculated per beat period. Results are verified using a piezo-electric transducer inline a fiber-under-test.
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 to our knowledge. The use of the geometric phase to extract strain makes it immune to polarisation diversity fading. This is because a polarisation mismatch between the interfering beams is not a hindrance to its measurement. The geometric phase is calculated using the amplitude of the beat signal and individual beam intensities without any need for phase unwrapping. It is measured per beat period and can be equated with the traditionally measured dynamic phase with appropriate scaling. The results show that the system based on the geometric phase successfully measures strain, free from polarisation mismatch fading and phase unwrapping errors, providing a completely novel solution to these problems.
This contribution introduces an investigation of a large-scale prestressed concrete bridge model (“BLEIB” structure at the BAM-TTS open air test site) by means of on-site cooperative measurements. This bridge has an external post-tensioning system and has been instrumented with the ultrasonic transducers, temperature sensors and optical fibers for Distributed Acoustic Sensing (DAS). Our experiment was designed to test the suitability of the novel 6C sensors developed within the framework of the GIOTTO project – the IMU50. The IMU50 sensor enables vibration measurements in translation along three axes and rotation around three axes. The geophone sensors were considered for complementary measurements of vertical velocity response. In the experiment, several perturbations were achieved by controlling the external influence factors such as loading and prestressing changes. The aim of the integrated measurement strategy was to fully observe the results of the condition change and to verify the effectiveness of multiple sensors for bridge monitoring.
Die verteilte faseroptische akustische Sensorik (DAS) wird vorgestellt, hinsichtlich ihrer Leistungsfähigkeit beschrieben und verschiedenste Anwendungsfelder, z.B. für das Zustandsmonitoring oder für seismische Messungen, beispielhaft gezeigt. Zudem werden mögliche Anwendungsfelder von DAS für den Kontext Kerntechnische Entsorgung (KTE) und Rückbau aufgezeigt.
We report, to our knowledge for the first time on simultaneous distributed temperature and strain sensing in a standard telecom optical fiber using a machine learning assisted Brillouin frequency domain analysis (BOFDA) system. The well-known temperature and strain cross-sensitivity problem is addressed by developing a BOFDA system with a high signal-to-noise ratio and applying machine learning. The spectrum consists of four highly resolved peaks, whose Brillouin frequency shifts are extracted and serve as features for the machine learning algorithms. The spectra result from a 450-m standard SMF-28 optical fiber, and particularly from a segment of 30 m. This fiber segment is coiled around a stretcher and placed in a climate chamber. The applied temperature and strain values range from 20 °C to 40 °C and from 0 µɛ to 1380 µɛ, respectively. The total measurement time to achieve a high SNR and resolve four peaks with a spatial resolution of 6 m is 16 min. To discriminate temperature and strain effects, simple frequentist and more sophisticated Bayesian-based algorithms are employed with the powerful Gaussian process regression (GPR) delivering the best performance in terms of temperature and strain errors, which are found to be 2 °C and 45 µɛ, respectively. These errors are calculated using leave-one-out cross-validation, so that an unbiased estimation of the sensor’s performance is provided.