ULTRASONIC IMAGING OF MATERIAL CONDITION USING ADVANCED SIMPLIFIED ULTRASONIC CT
Bibliographic record
Abstract
In this research, a new measurement method to estimate on infinitesimal change in material condition, the simplified ultrasonic CT system, which uses the information of three directions, that is, 90°, +45° and -45° to the inspection plane is proposed. The use of a simplified ultrasonic CT system has two merits: firstly, the measurement time is very short compared to a general CT; secondly, it can detect sensitively very infinitesimal defects in vertical or slant directions about the inspection plane because the obtained image is not a C scan image but a CT image calculated from three directions. Because of these merits, this method can be considered very effective for the evaluation of material condition. In order to know the applicability of actual NDT, several kinds of welded specimens were investigated. The results showed that the CT images obtained were very similar to the actual defect of specimens. Also, in order to confirm the performance of simplified ultrasonic CT, the D scan image by the TOFD method was obtained for the same specimen. The C scan or CT image gave better information than the D scan image obtained from TOFD method. In this research, the frequency analysis method for enhancing the C scan or CT image is developed. This frequency analysis method is based on the frequency response property of the material. By comparing the magnitude at frequency domain, the special frequency which shows the greatest difference between welded joint and base material was searched for and used to get a C scan or CT image.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".