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- Distributed acoustic sensing (5)
- Fiber optics sensors (3)
- Optical time domain reflectometry (3)
- Structural health monitoring (3)
- Artificial neural networks (2)
- DAS (2)
- Distributed fiber optic sensing (2)
- Distributed strain sensing (2)
- Electronic speckle pattern interferometry (2)
- Optical fiber sensor (2)
Organisationseinheit der BAM
A unique testing facility (KALFOS) using ESPI (electronic speckle pattern interferometery) as a referencing method has been realized for the characterisation of the strain transfer process from a component under load into surface applied fibre Bragg grating based strain sensors. The strain transfer mechanism can be described experimentally, while matching specific measurement requirements and environmental conditions.
Surface-applied fibre optic strain sensors were investigated using a unique validation facility equipped with application-independent optical reference systems. First, different adhesives for the sensor's application were analysed regarding their material properties. Measurements resulting from conventional measurement techniques, such as thermo-mechanical analysis and dynamic mechanical analysis, were compared with measurements resulting from digital image correlation, which has the advantage of being a non-contact technique. Second, fibre optic strain sensors were applied to test specimens with the selected adhesives. Their strain-transfer mechanism was analysed in comparison with conventional strain gauges. Relative movements between the applied sensor and the test specimen were visualized easily using optical reference methods, digital image correlation and electronic speckle pattern interferometry. Conventional strain gauges showed limited opportunities for an objective strain-transfer analysis because they are also affected by application conditions.
Fibre optic strain sensors used in practical applications have to provide reliable measurements. Therefore, the applied sensor and the sensor systems must be validated experimentally. This can be achieved with facilities which use physically independent measurement systems in order to avoid the influences caused by the application of a reference sensor. This paper describes the testing methods of the specially developed validation facility KALFOS for the qualification and evaluation of surface-applied strain sensors. For reliable sensor results, the performance of fibre optic strain patches with and without FBG under combined thermal and mechanical loading was investigated. Additionally, the strain gauge factor of the fibre optic strain patches with FBG was determined experimentally and compared to the specified strain gauge factor. These results will be the basis for the development of guidelines and standards concerning the application of the sensors.
Application of Intensity-Based Coherent Optical Time Domain Reflectometry to Bridge Monitoring
(2022)
Although distributed fiber sensing techniques have been widely used in structural health monitoring, the measurement results of bridge monitoring, particularly under destructive testing, have rarely been reported. To the best of our knowledge, this paper is the first report of distributed vibration measurement results, which we obtained during a three-day destructive test on an abolished bridge. A coherent optical time domain reflectometry (COTDR) was used to acquire the vibration information while the bridge was being sawed. The obtained signal was analyzed in time and frequency domain. Some characteristics of the sawing-induced vibration were retrieved by the short-time Fourier transform; the vibration exhibited several high frequency components within the measured range up to 20 kHz and all the components appeared in the same time slot. Some unexpected signals were also detected. Thorough analysis showed that they are quite different from the sawing-induced vibration and are believed to originate from internal damage to the bridge (probably the occurrence of cracks).
Distributed vibration sensing in optical fibers opened entirely new opportunities and penetrated various sectors from security to seismic monitoring. Here, we demonstrate a most simple and robust approach for dynamic strain measurement using wavelength-scanning coherent optical time domain reflectometry (C-OTDR). Our method is based on laser current modulation and Rayleigh backscatter shift correlation. As opposed to common single-wavelength phase demodulation techniques, also the algebraic sign of the strain change is retrieved. This is crucial for the intended applications in structural health monitoring and modal analysis. A linear strain response down to 47.5 pε and strain noise of 100 pε/√Hz is demonstrated for repetition rates in the kHz range. A field application of a vibrating bridge is presented. Our approach provides a cost-effective high-resolution method for structural vibration analysis and geophysical applications.
Wavelength-scanning distributed acoustic sensing for structural monitoring and seismic applications
(2019)
We introduce wavelength-scanning coherent optical time domain reflectometry (WS-COTDR) for dynamic vibration sensing along optical fibers. The method is based on spectral shift computation from Rayleigh backscatter spectra. Artificial neural networks (ANNs) are used for fast and high-resolution strain computation from raw measurement data. The applicability of the method is demonstrated for vibration monitoring of a reinforced concrete bridge. We demonstrate another application example for quasi-static and dynamic measurement of ground deformation and surface wave propagation along a dark fiber in a telecommunication cable.
A long distance range over tens of kilometers is a prerequisite for a wide range of distributed fiber optic vibration sensing applications. We significantly extend the attenuation-limited distance range by making use of the multidimensionality of distributed Rayleigh backscatter data: Using the wavelength-scanning coherent optical time domain reflectometry (WS-COTDR) technique, backscatter data is measured along the distance and optical frequency dimensions. In this work, we develop, train, and test deep convolutional neural networks (CNNs) for fast denoising of these two-dimensional backscattering results. The very compact and efficient CNN denoiser “DnOTDR” outperforms state-of-the-art image denoising algorithms for this task and enables denoising data rates of 1.2 GB/s in real time. We demonstrate that, using the CNN denoiser, the quantitative strain measurement with nm/m resolution can be conducted with up to 100 km distance without the use of backscatter-enhanced fibers or distributed Raman or Brillouin amplification.
We propose the use of alternating pulse wavelengths in a direct-detection coherent optical time domain reflectometry (C-OTDR) setup not only to measure strain and temperature changes but also to determine the correct algebraic sign of the change. The sign information is essential for the intended use in distributed mode shape analysis of civil engineering structures. Correlating relative backscatter signal shifts in the temporal/signal domain allows for measuring with correct magnitude and sign. This novel approach is simulated, experimentally implemented and demonstrated for temperature change measurement at a spatial resolution of 1 m.
We propose to use artificial neural networks (ANNs) for raw measurement data interpolation and signal shift computation and to demonstrate advantages for wavelength-scanning coherent optical time domain reflectometry (WS-COTDR) and dynamic strain distribution measurement along optical fibers. The ANNs are trained with synthetic data to predict signal shifts from wavelength scans. Domain adaptation to measurement data is achieved, and standard correlation algorithms are outperformed. First and foremost, the ANN reduces the data analysis time by more than two orders of magnitude, making it possible for the first time to predict strain in real-time applications using the WS-COTDR approach. Further, strain noise and linearity of the sensor response are improved, resulting in more accurate measurements. ANNs also perform better for low signal-to-noise measurement data, for a reduced length of correlation input (i.e., extended distance range), and for coarser sampling settings (i.e., extended strain scanning range). The general applicability is demonstrated for distributed measurement of ground movement along a dark fiber in a telecom cable. The presented ANN-based techniques can be employed to improve the performance of a wide range of correlation or interpolation problems in fiber sensing data analysis and beyond.