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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.
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.
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.
The paper presents an attempt for the calibration of an active
thermography method that is suitable for the non-destructive
evaluation of spot welds. Nowadays, the quality of spot welds is
commonly characterised by the application of random chisel tests,
which are time consuming, expensive and destructive. Recently a
non-destructive testing method by means of active thermography
was proposed that relies on the fact that the mechanical connection
formed by the spot weld also serves as a thermal bridge between
the two steel sheets joined in the welding process. It is shown in this
paper that this thermal bridge can be thermographically characterised
by extracting a measure for the spot weld diameter and hence the
quality of the spot weld. The determination of the absolute value
of the diameter hereby relies on a calibration of the testing system,
which is performed by means of X-ray computed tomography in this
study. The experiments were carried out using different experimental
approaches, namely transmission as well as reflection geometry
wSetup in reflectionith laser illumination. A comprehensive evaluation
of samples produced using different welding currents, hence different
quality, was carried out in order to validate the thermographic results.
Crack detection in steel bars at high surface temperatures is a critical problem in any manufacturing industry. Surface breaking cracks are the major problems during the billet casting. Many NDT techniques are proven its capability in crack detection at room temperature. Here, we are demonstrating the possibility of exposure of cracks using laser line thermography at higher surface temperatures (up to 600 °C). A continuous-wave (CW) laser is used to excite the sample kept at higher surface temperatures. The temperature distribution over the sample due to the laser line scanning is captured using a temperature calibrated infrared (IR) thermal camera. The response of the sample temperature in crack detection is investigated using a validated FE model. The impact of the oxide layer in crack detection is investigated by using two types of samples; one without any oxide layer and the second is with the oxide layer. The influence of laser power in the detection of defects at high temperatures is studied. 3D numerical models were developed for the cases; when the sample is with oxide layer and without any oxide layer for a better understanding of physics. The surface temperature rise due to laser heating is higher for the scaled sample compared to the no-scale sample. The presence of the oxide layer above the parent metal will reduce the reflectivity of the surface. Lower reflectivity will lead to increased absorption of incident energy so that the surface temperature rise will be higher than the surface with no scale. Thermal contrast linearly depends on laser power, which means higher laser power will increase the defect detectability even at a higher surface temperature.
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.