8.6 Faseroptische Sensorik
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- 8.6 Faseroptische Sensorik (237)
- 8.1 Sensorik, mess- und prüftechnische Verfahren (28)
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Im Rahmen der Integritätsbewertung einer zementierten 13 3/8" Rohrtour einer Sole-Produktionsbohrung wurden erstmals 2018 zeitgleich faseroptische Temperaturmessungen (DTS) und faseroptische Akustikmessungen (DAS) durchgeführt und ausgewertet. Dazu wurde die Bohrung zeitweise mit Stickstoff bespannt und wieder entlastet.
Industry 4.0 is all about interconnectivity, sensor-enhanced process control, and data-driven systems. Process analytical technology (PAT) such as online nuclear magnetic resonance (NMR) spectroscopy is gaining in importance, as it increasingly contributes to automation and digitalization in production. In many cases up to now, however, a classical evaluation of process data and their transformation into knowledge is not possible or not economical due to the insufficiently large datasets available. When developing an automated method applicable in process control, sometimes only the basic data of a limited number of batch tests from typical product and process development campaigns are available. However, these datasets are not large enough for training machine-supported procedures. In this work, to overcome this limitation, a new procedure was developed, which allows physically motivated multiplication of the available reference data in order to obtain a sufficiently large dataset for training machine learning algorithms. The underlying example chemical synthesis was measured and analyzed with both application-relevant low-field NMR and high-field NMR spectroscopy as reference method. Artificial neural networks (ANNs) have the potential to infer valuable process information already from relatively limited input data. However, in order to predict the concentration at complex conditions (many reactants and wide concentration ranges), larger ANNs and, therefore, a larger Training dataset are required. We demonstrate that a moderately complex problem with four reactants can be addressed using ANNs in combination with the presented PAT method (low-field NMR) and with the proposed approach to generate meaningful training data.
The ever more ambitious strategic goals of meeting the requirements in ensuring technical safety and security of civil structures have resulted in flourishing development of innovative structural health monitoring (SHM) technologies for early damage diagnosis and prognosis. At the same time, implementing SHM systems provides tangible economic benefits derived from lower life-cycle costs associated with reduction in the maintenance, repair and insurance expenses. Due to the large size and harsh environmental conditions common to most civil structures, the broad range of favorable physical-mechanical properties of POFs allow for customized monitoring solutions for a wide variety of applications.
In addition to common SHM-related advantages of optical fibers including their electromagnetic immunity, small size, lightweight as well as spark-free and non-conductive characteristics, POFs offer better bending and fracture resistance then their glass-counterparts. Particularly, the improved robustness of POFs, their ease of handling, low Young’s Modulus and high elastic limit of 10% compared to 1% in silica glass [1] are relevant to practical applications. Depending on the composition, dopants, drawing process and geometry [2], strain measurement up to 45% [3] or even above 100% [4,5] has been demonstrated with standard POFs. Therefore, the dominant market expected for POF sensors includes monitoring of high-strain-rate deformations in earthwork structures, crack detection in concrete and masonry structures [6] or overstressing in high-rise steel structures exposed to moisture, corrosion, leakage, fatigue, vibration, fire, overflow, earthquake and intentional damage. For fracture monitoring within concrete structures, the sensory usage of POFs becomes especially favorable since the extremely alkaline environment of concrete mixtures is well known to be corrosive to standard silica glass optical fibers (GOFs) [1,7].
Most of advanced distributed sensing techniques are commonly based on Rayleigh backscatter reflectometry using commercially available multimode (MM) POFs. Such typical MM POFs range from a step-index (SI) poly(methyl methacrylate) (PMMA) POF having a core diameter of 1 mm to a low-loss graded-index (GI) perfluorinated (PF) POF based on poly(perfluorobutenyl-vinylether) also known as CYTOP [8] with a 50 µm core diameter. The relatively low optical attenuation value of 30 dB/km at 1.3 µm [9,10] makes PFGI POFs also interesting for distributed Brillouin sensing [11-14]. Compared to GOFs, PFGI POFs offer better potential for temperature measurement and have comparably low theoretical attenuation limit [15]. Therefore, POF-based distributed Brillouin sensing is expected to play an important role in the future of SHM, especially at high-strain ranges. The significance of the Brillouin measurment technique can be also enhanced by further development of the single-mode (SM) POFs which are still subject of research and are used for coherent detection techniques [6]. Furthermore, SM PMMA POFs have been characterized in a Mach-Zehnder interferometer setup for strain values up to 15.8% [16,17].
The current development of SM perfluorinated and microstructured POFs (mPOFs) represents an immense promise for quasi-distributed dynamic measurement at high strain levels based on fiber Bragg grating (FBG) technology. While SM mPOFs with optical losses of about 1 dB/m can be fabricated [6], the SM PF POFs presented by Zhou et al. feature low attenuation of even less than 0.2 dB/m in the wavelength range of 1.41 µm to 1.55 µm [18]. At the same time, the SM PF POFs have the potential for improved thermal stability compared to their PMMA counterparts [19].
This whole chapter provides a comprehensive overview on current POF-based sensing principles and SHM technologies, highlighting their diverse applications in civil engineering structures. In the application-related context, close attention is paid to the development of smart sensor-based geotextiles and geogrids. Such geosynthetics-integrated distributed POF sensors have proven to be a promising solution for two- or even tree-dimensional monitoring of critical high mechanical deformations in both geotechnical and masonry structures. Moreover, geosynthetics in the form of nonwoven geotextiles as well as polymer-based geogrids used as carrier materials for POF sensors enable optimized load transfer from the monitored structure to the measuring fiber without losing their original functionality. In other words, smart geosynthetics provide a cost-efficient dual solution for, on the one hand, well-established increase of structure stability and decrease of erosion effects, on the other hand, early-warning and detection capabilities in the prevention and elimination of potential hazards and lasting damages.
Data set of low-field NMR spectra of continuous synthesis of nitro-4’-methyldiphenylamine (MNDPA). 1H spectra (43 MHz) were recorded as single scans.
Two different approaches for the generation of artificial neural networks training data for the prediction of reactant concentrations were used: (i) Training data based on combinations of measured pure component spectra and (ii) Training data based on a spectral model.
Synthetic low-field NMR spectra
First 4 columns in MAT-files represent component areas of each reactant within the synthetic mixture spectrum.
Xi (“pure component spectra dataset”)
Xii (“spectral model dataset”)
Experimental low-field NMR spectra from MNDPA-Synthesis
This data set represents low-field NMR-spectra recorded during continuous synthesis of nitro-4’-methyldiphenylamine (MNDPA). Reference values from high-field NMR results are included.
Der Mangel an Anwendungsrichtlinien und Validierungsverfahren für struktur-eingebettete faseroptische Dehnungssensoren, insbesondere auf Faser-Bragg-Gitter (FBG)-Basis, führte bislang dazu, dass diese Sensoren trotz ihrer hervorragenden Eigenschaften im Bereich der kommerziellen Material- und Strukturüberwachung nur in geringem Umfange eingesetzt wurden. Fragen zur Degradation der Sensoren unter Beanspruchung, Alterung durch klimatische Einflüsse und Enthaftung infolge Belastung der Struktur konnten bisher nur theoretisch simuliert oder anhand exemplarischer Proben für einzelne einflussnehmende Parameter im Labor untersucht werden. Die Erfassung des Sensorverhaltens im Bauteil unter komplexen Umwelteinflüssen während des Bauteilbetriebes, um damit eine Aussage zur Zuverlässigkeit der Sensormessdaten zu gewinnen, war bisher nicht möglich.
Im Forschungsprojekt FAMOS² wurde deshalb von 2014 bis 2018 die Realisierung eines Autodiagnoseverfahrens für faseroptische Dehnungssensoren erarbeitet, um die Funktionszuverlässigkeit und Langzeitstabilität der Sensoren während des Bauteilbetriebes innerhalb einer Bauteilstruktur bewerten zu können. Im Rahmen des Forschungsprojektes wurde gezeigt, dass ein FBG-Sensor mit einer speziell angepassten magnetostriktiven Schicht magnetisch so angeregt werden kann, dass mit einer zugeschnittenen Messmethodik zu jedem Zeitpunkt eine Bewertung der Sensorzuverlässigkeit unter Betriebsbedingungen möglich ist. Die auf den Sensor aufgebrachte magnetostriktive Schicht erzeugt bei Anregung mit einem passenden Magnetfeld eine gepulste, synthetische Dehnung. Diese Dehnung steht in einem definierten Verhältnis zum anregenden Magnetfeld und wird optisch über die Verschiebung der Bragg-Wellenlänge ausgelesen. Die Konstanz dieses Verhältnisses stellt dann ein Maß für die korrekte Funktionsfähigkeit des Sensors dar. Das Beschichtungs-verfahren, das magnetische Anregungs- und optische Ausleseverfahren, wie auch die Validierung des Sensors unter Berücksichtigung faseroptischer Effekte wurden während des Projekts konzeptionell entwickelt, aufgebaut und charakterisiert. Qualitativ kann mit diesem Verfahren zunächst eine Gut-/Schlecht-Beurteilung des Sensors vorgenommen werden. Perspektivisch bietet das Verfahren jedoch auch die Möglichkeit, verschiedene Versagensmechanismen bestimmen und klassifizieren zu können. Es zeichnete sich schon während des Projektverlaufs ab, dass sich aus den erzielten Ergebnissen über das Autodiagnoseverfahren hinaus weitere Anwendungsmöglichkeiten für den Einsatz des kombinierten magnetostriktiv-faseroptischen Sensorprinzips, beispielsweise als reiner Magnetfeldsensor, ergeben.
Nach Abschluss dieses Forschungsprojekts besteht nun die Möglichkeit, den Funktionszustand faseroptischer Dehnungssensoren jederzeit unabhängig von Alter, Belastung oder Kenntnis eines Referenzzustands zu einem bestimmten Zeitpunkt bestimmen zu können. Aufbauend auf diesen Ergebnissen können weiterführende Forschungen die Messmethodik vertiefend charakterisieren und weitere Anwendungsfälle erschließen.
Distributed acoustic sensing (DAS) over tens of kilometers of fiber optic cables is well-suited for monitoring extended railway infrastructures. As DAS produces large, noisy datasets, it is important to optimize algorithms for precise tracking of train position, speed, and the number of train cars, The purpose of this study is to compare different data analysis strategies and the resulting parameter uncertainties. We present data of an ICE 4 train of the Deutsche Bahn AG, which was recorded with a commercial DAS system. We localize the train signal in the data either along the temporal or spatial direction, and a similar velocity standard deviation of less than 5 km/h for a train moving at 160 km/h is found for both analysis methods, The data can be further enhanced by peak finding as well as faster and more flexible neural network algorithms. Then, individual noise peaks due to bogie clusters become visible and individual train cars can be counted. From the time between bogie signals, the velocity can also be determined with a lower standard deviation of 0.8 km/h, The analysis methods presented here will help to establish routines for near real-time Train tracking and train integrity analysis.
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.
Humidity is one of principal environmental parameters that plays an important role in various application areas. Distributed humidity/water sensing is sought after in wide range of applications including concrete condition monitoring in civil engineering, SHM of large structures such as dykes or dams, soil moisture measurement in agriculture or leak detection in pipeline or sewage industry. Using humidity-induced strain of specialty hygroscopic coating materials, such as polyimide (PI) seems as the most promising approach so far. In this work, relative humidity and temperature response of different commercial PI-coated and tight-buffer fibers is investigated for the development of distributed humidity sensor.
Das Teilprojekt zielt auf die Entwicklung integrierbarer verteilter faseroptischer Sensoren (u. a. verteilte Brillouin-Sensorik, verteilte akustische Sensorik) für die Langzeitüberwachung von Betriebsparametern in Hoch- und Mittelspannungskabelanlagen. Mit Hilfe der Sensoren sollen unzulässige Dehnungen, Übertemperaturen und das Eindringen von Feuchte, z. B. in Unterseekabeln, detektiert werden. Das Teilprojekt beinhaltet ebenfalls die Entwicklung integrierfähiger Sensoren für verteiltes (vibro-)akustisches Monitoring an Unterseekabeln, vor allem zur Lokalisierung und zur Abwendung von Störfällen und Schäden durch äußere mechanische Einflüsse (z. B. Ankerwurf).
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 results demonstrating several beneficial effects on distributed fiber optic vibration sensing (DVS) functionality and performance resulting from utilizing standard single mode optical fiber (SMF) with femtosecond laser-inscribed equally-spaced simple scattering dots. This modification is particularly useful when using traditional single-wavelength amplitude-based coherent optical time domain reflectometry (C-OTDR) as sensing method. Local sensitivity is increased in quasi-distributed interferometric sensing zones which are formed by the fiber segments between subsequent pairs of the scattering dots. The otherwise nonlinear transfer function is overwritten with that of an ordinary two-beam interferometer. This linearizes the phase response to monotonous temperature variations. Furthermore, sensitivity fading is mitigated and the demodulation of low-frequency signals is enabled. The modification also allows for the quantitative determination of local temperature gradients directly from the C-OTDR intensity traces. The dots’ reflectivities and thus the induced attenuation can be tuned via the inscription process parameters. Our approach is a simple, robust and cost-effective way to gain these sensing improvements without the need for more sophisticated interrogator technology or more complex fiber structuring, e.g., based on ultra-weak FBG arrays. Our claims are substantiated by experimental evidence.
X-ray reflectivity (XRR) is a powerful and popular scattering technique that can give valuable insight into the growth behavior of thin films. This study Shows how a simple artificial neural network model can be used to determine the thickness, roughness and density of thin films of different organic semiconductors [diindenoperylene, copper(II) phthalocyanine and alpha-sexithiophene] on silica from their XRR data with millisecond computation time and with minimal user input or a priori knowledge. For a large experimental data set of 372 XRR curves, it is shown that a simple fully connected model can provide good results with a mean absolute percentage error of 8–18% when compared with the results obtained by a genetic least mean squares fit using the classical Parratt formalism. Furthermore, current drawbacks and prospects for improvement are discussed.
Along temperature, humidity is one of the principal environmental factors that plays an important role in various application areas. Presented work investigates possibility of distributed fiberoptic humidity monitoring based on humidity-induced strain measurement in polyimide (PI)-coated optical fibers. Characterization of relative humidity (RH) and temperature response of four different commercial PI- and one acrylate-coated fiber was performed using optical backscattering reflectometry (OBR). The study addresses issues of temperature-humidity cross sensitivity, fiber response stability, repeatability, and the influence of annealing. Acrylate-coated fiber exhibited rather unfavorable nonlinear RH response with strong temperature dependence, which makes it unsuitable for humidity sensing applications. On the other hand, humidity response of PI-coated fibers showed good linearity with fiber sensitivity slightly decreasing at rising temperatures. In the tested range, temperature sensitivity of the fibers remained humidity independent. Thermal annealing was shown to considerably improve and stabilize fiber RH response. Based on performed analysis, a 20 m sensor using the optimal PI-coated fibers was proposed and constructed. The sensor uses dual sensing fiber configuration for mutual decoupling and simultaneous measurement of temperature and RH variations. Using OBR, distributed dual temperature-RH monitoring with cm spatial resolution was demonstrated for the first time.
We present our research on the development of a Brillouin optical frequency-domain analysis (BOFDA) using a perfluorinated graded-index polymer optical fiber (PFGI-POF) as a sensing fiber. The described works include investigations both on the selection of the setup components with respect to mode coupling effects and on the impact of the humidity cross-sensitivity. The suitability of the developed POF-based BOFDA is proved by a distributed measurement on an 86 m long PFGI-POF recorded with the spatial resolution of 6 m.
The influence of size effects on the thermoelectric properties of thin platinum films is investigated and compared to the bulk. Structural properties, like the film thickness and the grain size, are varied. We correlate the electron mean free path with the temperature dependence of the electrical conductivity and the absolute Seebeck coefficient SPt of platinum. A measurement platform was developed as a standardized method to determine SPt and show that SPt,film is reduced compared to SPt,bulk. Boundary and surface scattering reduce the thermodiffusion and the phonon drag contribution to SPt,film by nearly the same factor. We discuss in detail on behalf of a model, which describes the temperature dependence of the absolute Seebeck coefficient, the influence of size effects of electron-phonon and phonon-phonon interaction on SPt.