Filtern
Erscheinungsjahr
Dokumenttyp
- Beitrag zu einem Tagungsband (56)
- Vortrag (31)
- Zeitschriftenartikel (29)
- Posterpräsentation (13)
- Buchkapitel (9)
- Beitrag zu einem Sammelband (7)
- Dissertation (1)
Schlagworte
- Structural health monitoring (146) (entfernen)
Organisationseinheit der BAM
- 8 Zerstörungsfreie Prüfung (54)
- 8.6 Faseroptische Sensorik (28)
- 8.2 Zerstörungsfreie Prüfmethoden für das Bauwesen (18)
- 7 Bauwerkssicherheit (17)
- 7.2 Ingenieurbau (15)
- 8.4 Akustische und elektromagnetische Verfahren (13)
- 3 Gefahrgutumschließungen; Energiespeicher (9)
- 3.5 Sicherheit von Gasspeichern (7)
- 8.1 Sensorik, mess- und prüftechnische Verfahren (4)
- VP Vizepräsident (3)
Paper des Monats
- ja (2)
Eingeladener Vortrag
- nein (31)
Brücken sind Teil der alternden Verkehrsinfrastruktur. Um die Nutzungsdauer zu verlängern und plötzliche Schäden zu detektieren kann Bauwerksmonitoring ("Structural Health Monitoring") eingesetzt werden. Der Einfluss von Umgebungsbedingungen, beispielsweise der Temperatur, auf das Bauwerksverhalten ist meist größer als der Einfluss von Schäden. Diese Einflüsse bestmöglich voneinander zu trennen und Veränderungen im Tragverhalten korrekt Schäden oder Umgebungsbedingungen zuzuordnen ist eine offene Forschungsfrage. Diese Arbeit zeigt eine mögliche Lösung, bei der gekoppelte Modelle von Umwelteinflüssen, Schäden und Tragverhalten des Bauwerks auf Grundlage von Monitoringdaten aktualisiert werden. Das Framework dazu wird vorgestellt und an einem Laborexperiment eines Stahlbetonbalkens in der Klimakammer angewandt. Die Ergebnisse bestätigen die Vorgehensweise. In nächsten Schritten müssen komplexere Tragwerke und die Sensitivität des Ansatzes untersucht werden.
Guided wave ultrasonic features in composite overwrapped pressure vessels towards digital twin
(2023)
The digitalization of quality control processes and the underlying data infrastructures for safety relevant components, such as hydrogen pressure vessels, plays a significant role in the transition towards Industry 4.0. In the current safety regulations for hydrogen pressure vessels, there is no established concept for structural health monitoring. The development of a reliable structural health monitoring methodology for monitoring the structural integrity of pressure vessels enables a fast-forward transition from personnel- and costintensive recurring inspections, a.k.a. periodic maintenance, to predictive maintenance. In the work presented; we investigated the application of ultrasonic guided wave propagation to monitor and assess the condition of Type IV composite overwrapped pressure vessel (COPV). A sensor network of fifteen piezo-electric wafers is placed on the carbon fibre reinforced composite cylinder. Five different artificial damage configurations are created by gluing two different weight blocks on three different locations. The database containing measured guided wave data sets is enriched by two different boundary conditions. We utilized an open-source software, openBIS labnotebook, to store and analyse experimental datasets. The guided wave ultrasonic signals were investigated and analysed by using commonly used ultrasonic features (e.g., amplitude, frequency, time of flight) as well as non-traditional time-series features (kurtosis, skewness, variance). The features were used to calculate damage index and the detection performance for the results has been evaluated. The results suggest that both traditional and non-traditional features assume significant importance in artificial damage detection. The future works will additionally involve the impacts of operational conditions, such as periodic pressure variations temperature loadings as well as material degradations.
Wavelength scanning coherent optical time domain reflectometer (WS-COTDR) is a good candidate to spatially resolve the environmental information at comparatively low frequency. This paper reveals it can also work as a traditional optical time domain reflectometer (OTDR) to identify Fresnel reflection by averaging the obtained signal over the wavelength scanning range. Simultaneous distributed vibration sensing and a traditional OTDR measurement are experimentally demonstrated using the WS-COTDR system.
We report on the development of a field-proven distributed fiber optic sensing system for structural health monitoring in road construction and civil engineering. The system is based on a cost-efficient digital incoherent optical frequency domain reflectometry (I-OFDR) for distributed strain detection along a polymer optical fiber. In this method, the strain-induced backscatter increase in a graded-index multimode perfluorinated polymer optical fiber (PF-POF) is determined by measuring the complex transfer function of the sensing fiber using a compact digital data acquisition unit.
Wavelength scanning coherent optical time domain reflectometer (WS-COTDR) is a good candidate to spatially resolve the environmental information at comparatively low frequency. This paper reveals it can also work as a traditional optical time domain reflectometer (OTDR) to identify Fresnel reflection by averaging the obtained signal over the wavelength scanning range. Simultaneous distributed vibration sensing and a traditional OTDR measurement are experimentally demonstrated using the WS-COTDR system.
Introduction to group 8.6
(2023)
Understanding on how a machine learning model interprets data is a crucial step to verify its reliability and avoid overfitting. While the focus of the scientific community is nowadays orientated towards deep learning approaches, which are considered as black box approaches, this work presents a toolbox that is based on complementary methods of feature extraction and selection, where the classification decisions of the model are transparent and can be physically interpreted. On the example of guided wave benchmark data from the open guided waves platform, where delamination defects were simulated at multiple positions on a carbon fiber reinforced plastic plate under varying temperature conditions, the authors could identify suitable frequencies for further investigations and experiments. Furthermore, the authors presented a realistic validation scenario which ensures that the machine learning model learns global damage characteristics rather than position specific characteristics.
In non-destructive testing and structural health monitoring with ultrasonic waves, the quantification of damage in components is one of the main tasks. In many shell-like structures, such as plates, pipes, or laminate components, ultrasonic waves propagate as guided waves. Although guided waves enable the testing of large areas, their multimodal and dispersive properties make it challenging to analyze signals. So, there is a need for more advanced algorithms to handle these properties, especially when reconstructing damage position and geometry.
The reconstruction can be formulated as an inverse problem where the measured signals are fitted with a simulative forward model. Due to the small wavelength of ultrasonic waves, classic forward models based on, e.g., the Finite Element Method are computationally intensive. In contrast, the authors use the semi-analytical Scaled Boundary Finite Element Method (SBFEM) to reduce the computational effort. The SBFEM approximates arbitrary long, undamaged parts of the structure with only a few degrees of freedom.
This contribution summarizes a general inverse procedure based on algorithmic differentiation in combination with the SBFEM. Results are presented for damaged 2D cross-sectional models of waveguides. These results include an analysis of the robustness of the proposed algorithms against noise.