Ultrasonic Non-Destructive Testing (NDT) Using Wireless Sensor Networks
Bibliographic record
Abstract
This paper describes the integration of an ultrasonic-based non-destructive testing (NDT) with wireless sensor networks (WSNs) to continuously monitor material integrity during run-time. NDT is a technique that allows the examination of material properties without causing any damage to the material in the process. A wireless sensor network facilitates the collaborative effort to monitor a certain aspect without the need for expensive wired infrastructures. In this paper we describe the system architecture of a NDT system that is ultra low power, low cost, easy to use, and autonomously integrates into our WSN platform to collaboratively monitor the status conditions of industrial equipment. Our system was successfully deployed to monitor the thickness of a compound-metal (tungsten and steel) sheets used in vibration screens, which are utilized in the harsh industrial environments of the Oil-Sands, located in northern Alberta, Canada. The integration of the two technologies, WSN-based NDT, will bring about new applications in the field of low cost wireless material examination in real-time.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".