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Erscheinungsjahr
- 2018 (453) (entfernen)
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- Fundament (2)
- GMR (2)
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- Glasmalfarben (2)
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- Human error (2)
- Humidity (2)
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- Lattice Structures (2)
- Lattice structures (2)
- Luftgekoppelter Ultraschall (2)
- MRFA (2)
- Magneto-optischer Sensor (2)
- Maschinelles Lernen (2)
- Maschinennachgiebigkeit (2)
- Measurement uncertainty (2)
- Mercury intrusion porosimetry (2)
- Messtechnik (2)
- Metal matrix composite (2)
- Micro-reinforcement (2)
- Microcracking (2)
- Mobile elements (2)
- Mobile robot olfaction (2)
- Mobiles LIBS (2)
- Multigassensorik (2)
- Nasschemie (2)
- Non destructive testing (2)
- Non-destructive testing in civil engineering (2)
- Nuclear power plants (2)
- Numerical modeling (2)
- Opaque materials (2)
- Parkbauten (2)
- Passive thermography (2)
- Photogrammetry (2)
- Piezoresistive accelerometer (2)
- Plasma (2)
- Plasma reheating (2)
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- Plume (2)
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- Pores (2)
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- Rotorblatt (2)
- Rotorblattschalen (2)
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- SBFEM (2)
- Schichtdickenbestimmung (2)
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- Subsurface defects (2)
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- Surface cracks (2)
- Synchrotron X-ray refraction (2)
- Synchrotron X-ray refraction radiography (2)
- Tangential radiography (2)
- Temperature characteristics (2)
- Thermal wave (2)
- Thermoacoustic (2)
- Thermoacoustics (2)
- Thermoelectrics (2)
- Transducers (2)
- Ultrafast soliton fission (2)
- Ultraschallprüfung (2)
- Ultrasonics (2)
- Ultrasound Emission (2)
- Umweltsimulation (2)
- Vereinfachtes Verfahren (2)
- Verteilte Fasersensorik (2)
- Verteilte Messverfahren (2)
- Wall thickness measurement (2)
- Wandler (2)
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- Wirbelstromprüfung (2)
- Wireless mobile sensor device (2)
- X-ray (2)
- ZfPBau (2)
- Zuverlässigkeitstheorie (2)
- µ-CT (2)
- 3 DoF (1)
- 3D imaging (1)
- 3D-Verformungsmessung (1)
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- AGIL (1)
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- AM IN718 (1)
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- DIN EN ISO 17636 (1)
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Eingeladener Vortrag
- nein (175)
We propose a method based on artificial neural networks to extract strain information from wavelength-scanning coherent optical time domain reflectometry (C-OTDR) data. Our neural network algorithm performs more than two orders of magnitude faster than the conventional approach.
This is due to the highly parallel evaluation of the neural networks on a GPU accelerated computer and the fact that conventional correlation and interpolation analysis needs many Iteration steps. This opens the way for real-time C-OTDR strain sensing because the neural Network strain predictions require less time than the measurements themselves. Real-time data Analysis enables long-term sensing e.g. in structural health monitoring, because the large amount of raw data does not have to be stored but can immediately be reduced to the strain data of interest.
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.
The vulnerability of low-quality concrete of some bridges to ageing and deterioration while they are exposed to environmental conditions during their service life, influence of growing population and climate changes, is a well-known effect and requires survey. For survey, the development of a low cost, cost-efficient sensor network to be embedded for continuous or attached to the surface for periodic monitoring is essential.
Changing ground water conditions, flood or even leakage in fresh or disposal of waste water can lead to in-creased moisture content in building materials and structural elements as walls or floors. Moisture allows the transport of other adverse chemicals that might reduce the durability of structures. The paper presents a feasibility study about the capability of microwave modules as bluetooth® or ZigBee with frequency range at 2,4 GHz to create advanced Wireless Sensor Networks (WSN) for estimation and visualization of moisture distribution in infrastructure assets. It was found that the value of the received signal strength indication (RSSI) depends on the moisture content and can be the basis for the moisture distribution inside a massive structure.
The microwave modules may be used to compose networks outside and inside of building materials or structural elements. The higher the number of connections between BLE modules, the more precise and the more distant information can be obtained from the network. Mesh networking was applied to increase the quantitative information.
The main drawback in radiometric imaging is the degradation of the spatial resolution with increasing depth, which results in blurred images for deeper lying structures. We circumvent this degradation with blind structured illumination, combined with a non-linear joint sparsity reconstruction algorithm. We demonstrate this by imaging a line pattern and a star-shaped structure through a metal sheet with a resolution four times better than the width of the thermal point-spread-function. The ground-breaking concept of super-resolution can be transferred from optics to diffusive imaging by defining a thermal point-spread-function similar to the Abbe limit for a certain optical wavelength.
The detection of cracks before the failure is highly significant when it comes to safety-relevant structures. Crack detection in metallic samples at high surface temperature is one of the challenging situation in manufacturing industries.
Laser thermography has already proved its detection capability of surface cracks in metallic samples at room temperature. In this work a continuous wave (CW) laser use to generate a laser, which is using to scan the metal surface with notch.
The corresponding heat distribution on the surface monitored using infrared thermal (IR) camera. A simplified 3D model for laser thermography is developed and validated with experimental results. A dedicated image processing algorithm developed to improve the detectability of the cracks. To understand the dependency of surface temperature, laser power, laser scanning speed etc. in defect detection, we carried out parametric studies with our validated model. Here we Report the capability of laser thermography in crack detection at elevated temperature.
We examine the behavior of reinforced concrete components subjected to impact induced loading conditions which might be caused by vessels collisions such as aircraft fuel tanks The concrete plates were impact damaged at TU Dresden and shipped to BAM At BAM laminar tomography as the imaging method is used to determine and quantify the damage state An automatic crack detection method based on template matching is applied to find the cracks and we aim to develop a new method using machine learning Algorithms In addition numerical models are developed to understand the experiment and to predict the damage structures based on failure mechanisms.
X-ray scatter imaging is a well-established NDT technique to inspect complex objects using only a single-sided access. We present a specially designed multi-slit scatter camera consisting of several twisted slits which are parallelly arranged in a metal block. The camera projects one image per slit to the digital detector array, where the images are overlaying each other. The aperture is corrected based on a de-convolution algorithm to focus the overlaying projections into a single representation of the object. To achieve high scatter intensities from an object, it is necessary to optimize the parameters of the scatter system by simulation.
In der anthropologischen Rudolf-Virchow-Sammlung der Berliner Gesellschaft für Anthropologie, Ethnologie und Urgeschichte (BGAEU) befindet sich eine größere Anzahl menschlicher Schädel aus dem Gebiet des heutigen Lettlands, die Mehrzahl dabei von der im Norden Lettlands am Burtnieksee gelegenen Fundstelle Riņņukalns. Der nachfolgende Aufsatz beschreibt die Gründe, warum diese Stücke in den 1870er Jahren in die Sammlung gelangt sind, und präsentiert eine anthropologische Dokumentation und Analyse der Schädelfunde vom Riņņukalns aus der Sammlung.
A novel approach for rating fatigue-initiating inclusions in highly demanding steel (INCAFAT)
(2018)
INCAFAT project aimed to improve existing fatigue damage models by establishing the most suitable combination of measurement techniques to characterise harmful inclusion populations in highly demanding steels. The different inclusion assessments carried out confirm that, chemical composition, secondary metallurgy and manufacturing route affect content, nature, size and shape of inclusions. According to the FEM model, inclusions produce an alteration of the stress field in their surrounding region, which can promote a fatigue failure. Experimental work on fatigue testing has demonstrated that depending on the stressed direction fatigue failures in highly demanding steels could be produced by different types of inclusions. Fractography analyses confirmed that meso-inclusions harmful in fatigue cannot be rated by standard methods, nor 10 MHz ultrasonic testing (macro) or micro-cleanness assessments. The necessity of rating these meso-inclusions has led to critical evaluation of Extreme Value Analysis according to ASTM E2283-08 and the development of high frequency immersion ultrasonic testing. EVA methodology based on inclusion width can be applied reliably when principal stress is parallel to the rolling direction. On the contrary, if inclusions are testing in the elongated directions its fails. On the other hand, the guidelines and recommendations for high frequency ultrasonic testing have been compiled in a new European standard draft. This method based on focal beam probes and high-resolution devices is able to provide information on meso-inclusion distribution.
Der Beitrag präsentiert die erarbeiteten technischen Richtlinien zur Anwendung und Prüfung von Multigassensoren innerhalb der Richtlinienreihe VDI/VDE 3518 sowie in diesem Zusammenhang die Möglichkeiten der Sensorprüfung im akkreditierten Prüflabor des Fachbereichs 8.1 der BAM. Im Speziellen wird das in Kürze veröffentlichte Blatt 3 der Richtlinienreihe vorgestellt, das Bezug auf Multigassensoren für geruchsbezogene Messungen mit elektronischen Nasen nimmt.