A Distributed Reflector Localization Approach to Ultrasonic Array Imaging in Non-Destructive Testing Applications
Why this work is in the frame
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Bibliographic record
Abstract
In array-based immersion ultrasonic non-destructive testing (NDT), an ultrasonic array and a solid test sample are immersed in water for the purpose of imaging and flaw detection inside the test sample. In such a test scenario, the upper surface of the test sample has two effects: i) it produces a strong interference signal in the backscattered received signal, and ii) its shape determines the array spatial signature of every point inside the material under test. Hence, in immersion NDT, to achieve a precise localization of a crack inside a test sample, the knowledge of the shape of the upper surface of the test sample is required. In this paper, we propose a distributed reflector modeling approach to characterize the interface between water and a solid test sample as well as any crack inside the solid test sample. This approach relies on the so-called incoherently distributed reflector modeling, where a distributed reflector can be modeled as infinitely many point sources located close to each other. Using such an approach, we present a model for the array data, and then develop a covariance fitting based technique to estimate the parameters of the shape of the interface between the two media and those of the shape of a crack inside the test material. Our numerical experiments show that our proposed approach yields a lower root mean squared error for the parameter estimates, compared to a state-of-the-art method, called root mean squared velocity technique.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it