Filtern
Erscheinungsjahr
Dokumenttyp
- Beitrag zu einem Tagungsband (35)
- Vortrag (26)
- Posterpräsentation (13)
- Buchkapitel (7)
- Beitrag zu einem Sammelband (7)
- Zeitschriftenartikel (5)
- Dissertation (1)
Referierte Publikation
- nein (94) (entfernen)
Schlagworte
- Structural health monitoring (94) (entfernen)
Organisationseinheit der BAM
- 8 Zerstörungsfreie Prüfung (33)
- 8.6 Faseroptische Sensorik (17)
- 7 Bauwerkssicherheit (11)
- 7.2 Ingenieurbau (11)
- 8.2 Zerstörungsfreie Prüfmethoden für das Bauwesen (11)
- 8.4 Akustische und elektromagnetische Verfahren (5)
- VP Vizepräsident (3)
- VP.1 eScience (3)
- 3 Gefahrgutumschließungen; Energiespeicher (2)
- 3.0 Abteilungsleitung und andere (2)
Eingeladener Vortrag
- nein (26)
A dynamic and quasi-distributed sensor principle for simultaneous measurement of length changes and optical power changes between reflection points in an optical fiber is presented. The technique is based on the incoherent optical frequency domain reflectometry (I-OFDR). Length change resolutions < 1 µm and measurement repetition rates up to 2 kHz can be achieved using standard single-mode and multi-mode optical fibers. Simultaneous length change and refractive index measurement as well as field test results showing the deformation of a masonry building under seismic load are presented. Promising fields of application for this technique are the structural health monitoring sector and chemical process control.
Support structures of wind turbines in German offshore wind farms are regularly inspected. Currently, inspection outcomes are generally not systematically recorded. This prevents their consistent handling and processing, which is a key requirement to enable an efficient structural integrity management. As part of the DiMoWind-Inspect project, a data model and reference designation system for such inspection results is developed to facilitate their identification, localization, quantification, tracing and linking throughout the lifetime of a wind farm and beyond. The inspection results together with structural health monitoring results and information on repairs form the basis for assessing and predicting the structural condition, estimating the remaining lifetime, and planning of future inspections, structural health monitoring, and repairs. As a basis for developing a digital structural integrity management, a generic framework is proposed in this paper, which describes the stakeholders, data, models, processes and workflows of the integrity management of support structures in offshore wind farms and their interrelations. The framework adopts a building information modelling approach to describe the information relevant to the structural integrity management. The central digital space of the framework is a common data environment. An implementation of the framework will enable a digital structural integrity management in which inspection, structural health monitoring, repair, assessment and planning outcomes generated throughout the life cycle of a wind farm can be consistently collected, managed, shared and processed by the relevant shareholders.
The applications of composite overwrapped pressure vessels (COPVs) in extreme conditions, such as storing hydrogen gases at very high pressure, impose new requirements related to the system's integrity and safety. The development of a structural health monitoring (SHM) system that allows for continuous monitoring of the COPVs provides rich information about the structural integrity of the component. Furthermore, the collected data can be used for different purposes such as increasing the periodic inspection intervals, providing a remaining lifetime prognosis, and also ensuring optimal operating conditions. Ultimately this information can be complementary to the development of the envisioned digital twin of the monitored COPVs. Guided waves (GWs) are preferred to be used in continuous SHM given their ability to travel in complex structures for long distances. However, obtained GW signals are complex and require advanced processing techniques. Machine learning (ML) is increasingly utilized as the main part of the processing pipeline to automatically detect anomalies in the system's integrity. Hence, in this study, we are scrutinizing the potential of using ML to provide continuous monitoring of COPVs based on ultrasonic GW data. Data is collected from a network of sensors consisting of fifteen Piezoelectric (PZT) wafers that were surface mounted on the COPV. Two ML algorithms are used in the automated evaluation procedure (i) a long short-term memory (LSTM) autoencoder for anomaly detection (defects/impact), and (ii) a convolutional neural network (CNN) model for feature extraction and classification of the artificial damage sizes and locations. Additional data augmentation steps are introduced such as modification and addition of random noise to original signals to enhance the model's robustness to uncertainties. Overall, it was shown that the ML algorithms used were able to detect and classify the simulated damage with high accuracy.
We present a novel technique for dynamic and simultaneous measurement of displacement and refractive indices at multiple reflection points in optical fibers. This quasi-distributed sensor is based on the incoherent optical frequency domain reflectometry (I-OFDR) technique and allows for m-resolution length change measurement and precise refractive index measurement. We show that the dynamic measurement ability and the simple sensor design allows for new applications in the field of structural health monitoring and chemical process control.
A novel quasi-distributed long-gauge fiber optic strain sensor system for dynamic measurement
(2011)
We present a novel technique based on incoherent optical frequency domain reflectometry (OFDR) to measure length changes quasi-distributed between reflection points in optical fibres. The technique enables length changes to be measured with a resolution better than 1 µm and allows for static and dynamic measurement capabilities up to 2 kHz. We demonstrate that dynamic measurements of multiple fibre sections can be conducted independently from each other with high precision. Due to the precise and dynamic measurement capabilities, the proposed sensor system is expected to open new fields of application, especially in the structural-health-monitoring sector. Possible applications are discussed in the paper.
Acoustic emission
(2013)