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Impact damages and delaminations in fibre-reinforced composites (FRC) might not be visible at the surface, but could have an influence on the resistance and on the long-term behaviour of the component. Therefore, and especially for safety relevant structures, non-destructive methods are required for the assessment of such damages.
Active thermography methods are suitable to characterize damages after loading using different kind of excitation techniques and various configurations of infrared (IR) camera and heating sources. Here, flash lamps, impulse excitation with infrared radiator and lock-in technique with halogen lamps or widened laser beams are suited. In addition, non-optical sources like sonotrodes (requiring direct contact to the structure) or induction generators (only suited for carbon fibre reinforced polymer (CFRP) structures) could be applied as well. For the investigation of the evolution of the damage during the impact, passive thermography can be applied in-situ. Elastic and plastic deformations alter the temperature of the structure and thus the temperature on the surface.
In this contribution, at first the general principles of quantitative defect characterisation in FRC using active thermography with flash, impulse and lock-in excitation are described. Optical and thermal properties of the FRC material and its anisotropy are considered. Results of phase differences obtained at flat bottom holes with flash and lock-in thermography are compared for qualifying both methods for quantitative defect characterization. Secondly, the damage evolution of CFRP and GFRP structures under impact load and static tensile loading is described. The spatial and temporal evolution of the surface temperature enables us to distinguish matrix cracks or fibre-matrix separation from delaminations between the layers. Afterwards, all results for loading defects, obtained by passive and active thermography, are compared with each other. Fig. 1 and 2 show the difference of passive and flash thermography obtained at impact and tensile loaded CFRP plates, respectively. As one purpose of these investigations is the development of standards within national (DIN) and European (CEN) standardisation bodies, new draft and final standards are presented and further needs are discussed at the end of the presentation.
We report on recent developments in the detection of surface breaking cracks using
flying laser spot thermography. Application of an infrared camera for mapping the
thermal radiation after excitation with a diode laser equipped with an optical scanner
allows us to examine a surface containing cracks in an entirely non-destructive,
contactless and fast way, without even moving the camera. We developed an efficient
and robust algorithm that can be applied directly to the recorded thermal sequences,
and that derives a single image containing all crack signatures. For this crack detection
technique, no specific synchronisation between laser and camera is required. Hence,
our approach is suitable for an upgrade of existing thermographic systems. The
feasibility of the proposed procedure is proven by testing an artificial test sample and a
piece of rail that comprises roll contact fatigue cracks and by comparing the results
with magnetic particle testing.
Catastrophic optical damage (COD) is analyzed during single current pulse excitation of 975 nm emitting diode lasers. Power transients and thermal images are monitored during each pulse. The COD process is unambiguously related to the occurrence of a thermal flash of Plancks radiation. We observe COD to ignite multiple times in subsequent pulses. Thermography allows for tracing a spatial motion of the COD site on the front facet of the devices. The time constant of power decay after the onset of COD has values from 400 to 2000 ns, i.e., an order of magnitude longer than observed for shorter-wavelength devices.
Single-pulse tests of the catastrophic optical damage (COD) are performed for three batches of diode lasers with different gain-regions. The tests involve in situ inspection of front, rear, and side of the devices by a thermocamera. Devices with an Al-containing gain-region show COD at the front facet, as expected for strong facet heating via surface recombination and reabsorption of laser light. In contrast, Al-free devices with low surface recombination rates tend to fail at the rear facet, pointing to a different heating scenario. The high carrier density at the rear facet favors heating and COD via Auger recombination processes.
Double-side cooled high-power diode laser bars packaged by different techniques on different types of passive heat sinks are analyzed in terms of packaging-induced strain. Reference data from standard devices being single-side cooled only and packaged by conventional soft and hard soldering are also presented. Thermal profiling across the devices complements the results. The most suitable packaging architecture and technique for double-side cooled bars is identified. Measurements of the laser emission near field and electroluminescence pattern provide direct reference to the functionality of the devices. Furthermore, a type of cross calibration of the methods used for strain analysis is made, since all techniques are applied to the same set of bars. This involves micro photoluminescence, micro Raman, and degree-of-polarization electroluminescence spectroscopy.
This article presents deep unfolding neural networks to handle inverse problems in photothermal radiometry enabling super-resolution (SR) imaging. The photothermal SR approach is a well-known technique to overcome the spatial resolution limitation in photothermal imaging by extracting high-frequency spatial components based on the deconvolution with the thermal point spread function (PSF). However, stable deconvolution can only be achieved by using the sparse structure of defect patterns, which often requires tedious, handcrafted tuning of hyperparameters and results in computationally intensive algorithms. On this account, this article proposes Photothermal-SR-Net, which performs deconvolution by deep unfolding considering the underlying physics. Since defects appear sparsely in materials, our approach includes trained block-sparsity thresholding in each convolutional layer. This enables to super-resolve 2-D thermal images for nondestructive testing (NDT) with a substantially improved convergence rate compared to classic approaches. The performance of the proposed approach is evaluated on various deep unfolding and thresholding approaches. Furthermore, we explored how to increase the reconstruction quality and the computational performance. Thereby, it was found that the computing time for creating high-resolution images could be significantly reduced without decreasing the reconstruction quality by using pixel binning as a preprocessing step.
Learned block iterative shrinkage thresholding algorithm for photothermal super resolution imaging
(2022)
Block-sparse regularization is already well known in active thermal imaging and is used for multiple-measurement-based inverse problems. The main bottleneck of this method is the choice of regularization parameters which differs for each experiment. We show the benefits of using a learned block iterative shrinkage thresholding algorithm (LBISTA) that is able to learn the choice of regularization parameters, without the need to manually select them. In addition, LBISTA enables the determination of a suitable weight matrix to solve the underlying inverse problem. Therefore, in this paper we present LBISTA and compare it with state-of-the-art block iterative shrinkage thresholding using synthetically generated and experimental test data from active thermography for defect reconstruction. Our results show that the use of the learned block-sparse optimization approach provides smaller normalized mean square errors for a small fixed number of iterations. Thus, this allows us to improve the convergence speed and only needs a few iterations to generate accurate defect reconstruction in photothermal super-resolution imaging.
We present a systematic study on the performance of laser-thermography for the detection of surface cracks in metallic components. Scanning a metallic surface with laser causes local heating that is mapped simultaneously by an IR-camera and allows identifying cracks with sub-µm openings. The detectability, however, depends on a number of acquisition parameters (e.g. scanning speed, laser power, IR-camera resolution) that typically relate on each other. Most importantly, the detection-sensitivity of surface breaking cracks is given by a particular combination for the acquisition parameter values. As a result, this sensitivity is adaptable within wide ranges allowing the detection of cracks with openings ranging from 200 to 0.1 µm at testing speeds of 100 to 0.05 cm²/s. By examining artificial as well as fatigue cracks, we demonstrate that the method can be even applied to shiny surfaces with no need of pretreatments, which makes it an entirely contactless, remote and automatable NDT technique. A comparison with magnetic particle testing shows that laser-thermography has the potential to become a strong competitor to conventional surface inspection methods in the future.
Mechanisms and fast kinetics of the catastrophic optical damage (COD) in GaAs-based diode lasers
(2011)
COD diagram determined for a batch of broad-area AlGaAs diode lasers. The time to COD within a single current pulse is plotted versus the actual average optical power in the moment when the COD takes place. Full circles stand for clearly identified COD events (right ordinate), whereas open circles (left ordinate) represent the pulse duration in experiments, where no COD has been detected. A borderline (gray) exists between two regions, i. e., parameter sets, of presence (orange) and absence of COD (blue). This borderline is somewhat blurred because of the randomness in filamentation of the laser nearfield and scatter in properties of the involved individual devices.
The early stages of catastrophic optical damage (COD) in 808 nm emitting diode lasers are mapped by simultaneously monitoring the optical emission with a 1 ns time resolution and deriving the device temperature from thermal images. COD occurs in highly localized damage regions on a 30 to 400 ns time scale which is determined by the accumulation of excess energy absorbed from the optical output. We identify regimes in which COD is avoided by the proper choice of operation parameters.