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We present an all-purpose crack detection algorithm for flying spot thermography which is directly applicable to a thermogram sequence without the need of any additional information about the experimental setup. A single image containing distinct crack signatures is derived in two steps. Firstly, the spatial derivative is calculated for each frame of the sequence and, secondly, the resulting data set is sorted pixel wise along the time axis. The feasibility of the proposed procedure is proven by testing a piece of rail that comprises roll contact fatigue cracks and by comparing the results with magnetic particle testing.
Impulse and lock-in thermography have been applied to detect delaminations of prototype solder joints, similar to those to be produced between Cu shunts and Cu busbar stabilisers at the Large Hadron Collider (LHC) at CERN. Two infrared cameras with different detector materials and with different spectral ranges and two excitation techniques have been tested and compared for their ability to detect delaminations behind 2 and 3 mm thick Cu shunts. We have analyzed the signal to noise ratio (SNR) for each detected defect and are able to detect defects down to a nominal edge length of 4 mm behind 2 mm thick Cu shunts by using fast impulse thermography and a camera with a microbolometer array. For the 3 mm thick Cu shunt, on the other hand, the nominal 4 mm defect is only visible in the lock-in thermography phase images and the highest SNR has been achieved with a cooled InSb-based camera. In addition, numerical simulations show the influence of the minimum detectable defect size on the shunt thickness and that the developed on-site testing technique is sufficient to find all defects that are detectable theoretically.
The coherent superposition of two anti-phased thermal wave fields creates a zone of destructive interference which is extremely sensitive to the presence of defects without any reference measurements.
Combining a high power laser with a spatial light modulator allows modulating phase and amplitude of an illuminated surface that induces spatially and temporally controlled thermal wave fields. The position and depth of defects are reconstructed from analysis of the Amplitude and Phase of the resulting photothermal signal. The proposed concept is experimentally validated and supported by numerical modeling.
For the last 20 years active thermography has developed into a standard method in non-destructive material testing. It has become possible to detect defects such as cracks, voids, or even material inhomogeneities. Until now, it is still difficult to quantify subsurface or hidden defects in size due to the diffusive nature of heat flow within a solid. Facing this issue, lockin thermography and other photothermal techniques have been established. They are based on exciting a sample periodically (e.g. with a halogen lamp), causing a controlled periodical heat flow and thereby representing strongly damped thermal waves. These techniques make use of interference and reflection of thermal waves which allow enhancing depth resolution.
So far, only the temporal component of the light source was modified to achieve a defined vertical heat flow – In contrast, we propose a novel technique in which we are able to control both: time and space. This technique enables us to exploit the possibilities of coherent thermal wave shaping. We achieve that by combining a spatial light modulator (SLM) with a high power laser. This approach allows us to launch a set of individually controlled and fully coherent high energy thermal waves into the sample volume. That means, we intentionally use wave propagation throughout the sample’s material in both - vertical and lateral direction. As one possible application, we use a thermal waves’ interference effect of two phase shifted wave patterns to detect the position of hidden defects. The wave patterns are positioned with a certain distance and a 180° phase shift to each other creating an amplitude depletion zone right in the middle of the two patterns. When a defect is brought unsymmetrically into the depletion zone, the lateral heat flow is disturbed. If the sample is now moved through the depletion zone, a defect can be easily characterized. Exciting periodically while controlling simultaneously phase and amplitude enables us to have a defined thermal wave propagation throughout the sample which means thermal waves can be controlled almost like acoustical or optical waves. This offers the opportunity to transfer known technologies from wave shaping techniques to thermography methods.
The method described here allows to determine the size of the thermal contact between two metal sheets joined by spot welding. This size is a measure for the size of the weld nugget, i.e. the zone melted during the welding process, and thus the quality of the welded joint. The method applies active thermography in transmission or reflection setup. Especially the reflection setup offers an attractive possibility for non-destructive testing when components can be accessed from one side only. The spot weld region is optically heated by laser or flash light radiation. The weld nugget provides the mechanical joint, but also constitutes a thermal bridge between the two welded sheets. The latter will be exploited in this method. The better thermal contact at the weld Nugget contrasts with the surrounding material, where the heat transfer between the two sheets is comparatively low. A major advantage of the described method is the applicability on sheets without any surface treatment. This is achieved by a proper normalization of the data, allowing for a correction of the varying surface emissivity.
Spatial and temporal control of thermal waves by using DMDs for interference based crack detection
(2016)
Active Thermography is a well-established non-destructive testing method and used to detect cracks, voids or material inhomogeneities. It is based on applying thermal energy to a samples’ surface whereas inner defects alter the nonstationary heat flow. Conventional excitation of a sample is hereby done spatially, either planar (e.g. using a lamp) or local (e.g. using a focused laser) and temporally, either pulsed or periodical. In this work we combine a high power laser with a Digital Micromirror Device (DMD) allowing us to merge all degrees of freedom to a spatially and temporally controlled heat source. This enables us to exploit the possibilities of coherent thermal wave shaping. Exciting periodically while controlling at the same time phase and amplitude of the illumination source induces – via Absorption at the sample’s surface - a defined thermal wave propagation through a sample. That means thermal waves can be controlled almost like acoustical or optical waves. However, in contrast to optical or acoustical waves, thermal waves are highly damped due to the diffusive character of the thermal heat flow and therefore limited in penetration depth in relation to the achievable resolution. Nevertheless, the coherence length of thermal waves can be chosen in the mmrange for modulation frequencies below 10 Hz which is perfectly met by DMD technology. This approach gives us the opportunity to transfer known technologies from wave shaping techniques to thermography methods. We will present experiments on spatial and temporal wave shaping, demonstrating interference based crack detection.
Subsurface defect localization by structured heating using laser projected photothermal thermography
(2017)
The presented method is used to locate subsurface defects oriented perpendicularly to the surface. To achieve this, we create destructively interfering thermal wave fields that are disturbed by the defect. This effect is measured and used to locate the defect. We form the destructively interfering wave fields by using a modified projector. The original light engine of the projector is replaced with a fiber-coupled high-power Diode laser. Its beam is shaped and aligned to the projector's spatial light modulator and optimized for optimal optical throughput and homogeneous projection by first characterizing the beam profile, and, second, correcting it mechanically and numerically. A high-performance infrared (IR) camera is set up according to the tight geometrical situation (including corrections of the geometrical image distortions) and the requirement to detect weak temperature oscillations at the sample surface. Data acquisition can be performed once a synchronization between the individual thermal wave field sources, the scanning stage, and the IR camera is established by using a dedicated experimental setup which needs to be tuned to the specific material being investigated. During data post-processing, the relevant information on the presence of a defect below the surface of the sample is extracted. It is retrieved from the oscillating part of the acquired thermal radiation coming from the so-called depletion line of the sample surface. The exact location of the defect is deduced from the analysis of the spatial-temporal shape of these oscillations in a final step. The method is reference-free and very sensitive to changes within the thermal wave field. So far, the method has been tested with steel samples but is applicable to different materials as well, in particular to temperature sensitive materials.
Learned block iterative shrinkage thresholding algorithm for photothermal super resolution imaging
(2020)
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. To avoid time-consuming manually selected regularization parameters, we propose a learned block-sparse optimization approach using an iterative algorithm unfolded into a deep neural network. More precisely, we show the benefits of using a learned block iterative shrinkage thresholding algorithm that is able to learn the choice of regularization parameters. In addition, this algorithm enables the determination of a suitable weight matrix to solve the underlying inverse problem. Therefore, in this paper we present the algorithm and compare it with state of the art block iterative shrinkage thresholding using synthetically generated test data 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 than without learning. Thus, this new approach allows to improve the convergence speed and only needs a few iterations to generate accurate defect reconstruction in photothermal super resolution imaging.
We combine three different approaches to greatly enhance the defect reconstruction ability of active thermographic testing. As experimental approach, laser-based structured illumination is performed in a step-wise manner. As an intermediate signal processing step, the virtual wave concept is used in order to effectively convert the notoriously difficult to solve diffusion-based inverse problem into a somewhat milder wavebased inverse problem. As a final step, a compressed-sensing based optimization procedure is applied which efficiently solves the inverse problem by making advantage of the joint sparsity of multiple blind measurements. To evaluate our proposed processing technique, we investigate an additively manufactured stainless steel sample with eight internal defects. The concerted super resolution approach is compared to conventional thermographic reconstruction techniques and shows an at least four times better spatial resolution.