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- 2019 (3) (entfernen)
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- Englisch (3) (entfernen)
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- Thermography (3)
- Blind structured illumination (1)
- Heat diffusion (1)
- Laser (1)
- Laser thermography (1)
- NDT (1)
- Photothermal (1)
- Structured heating (1)
- Subsurface defects (1)
- Super resolution (1)
Organisationseinheit der BAM
Photothermal radiometry with an infrared camera allows the contactless temperature measurement of multiple surface pixels simultaneously. A short light pulse heats the sample. The heat propagates through the sample by diffusion and the corresponding temperature evolution is measured at the sample’s surface by an infrared camera. The main drawback in radiometric imaging is the loss of the spatial resolution with increasing depth due to heat diffusion, which results in blurred images for deeper lying structures. We circumvent this information loss due to the diffusion process by using blind structured illumination, combined with a non-linear joint sparsity reconstruction algorithm. The structured illumination is realized by parallel laser lines from a vertical-cavity surface-emitting laser (VCSEL) array controlled by a random binary pattern generator. By using 150 different patterns of structured illumination and our iterative joint sparsity algorithm, it was possible to resolve 1 mm thick lines at a distance down to 0.5 mm, which results in a resolution enhancement of approximately a factor of four compared to the resolution of 5.9 mm for homogenous illuminated thermographic reconstruction.
We report on photothermal detection of subsurface defects by coherent superposition of thermal wave fields. This is made possible by structured heating using high-power VCSEL laser arrays whose individual emitter groups can be arbitrarily controlled. In order to locate the defects, we have developed a scanning method based on the continuous wavelet transformation with complex Morlet wavelet using the destructive interference effect of thermal waves. This approach can also be used for thermally very fast and highly reflective materials such as uncoated aluminum. We show that subsurface defects at an aspect ratio of defect width to defect depth down to 1/3 are still detectable in this material.
The separation of two closely spaced defects in fields of Thermographic NDE is very challenging. The diffusive nature of thermal waves leads to a fundamental limitation in spatial resolution. Therefore, super resolution image reconstruction can be used. A new concerted ansatz based on spatially structured heating and joint sparsity of the signal ensemble allows for an improved reconstruction of closely spaced defects. This new technique has been studied using a 1D laser array with randomly chosen illumination pattern.
This paper presents the results after applying super resolution algorithms, such as the iterative joint sparsity (IJOSP) algorithm, to our processed measurement data. Different data processing techniques before applying the IJOSP algorithm as well as the influence of regularization parameters in the data processing techniques are discussed. Moreover, the degradation of super resolution reconstruction goodness by the choice of experimental parameters such as laser line width or number of measurements is shown.
The application of the super resolution results in a spatial resolution enhancement of approximately a factor of four which leads to a better separation of two closely spaced defects.