Implementation of an on-line monitoring system for transmitters in a CANDU nuclear power plant
Bibliographic record
Abstract
Many transmitters (pressure, level and flow) are used in a nuclear power plant. It is necessary to calibrate them periodically to ensure that their measurements are accurate. These calibration tasks are time consuming and often contribute to worker radiation exposure. Human errors can also sometimes degrade their performance since the calibration involves intrusive techniques. More importantly, experience has shown that the majority of current calibration efforts are not necessary. These facts motivated the nuclear industry to develop new technologies for identifying drifting instruments. These technologies, well known as on-line monitoring (OLM) techniques, are non-intrusive and allow focusing the maintenance efforts on the instruments that really need a calibration. Although few OLM systems have been implemented in some PWR and BWR plants, these technologies are not commonly used and have not been permanently implemented in a CANDU plant. This paper presents the results of a research project that has been performed in a CANDU plant in order to validate the implementation of an OLM system. An application project, based on the ICMP algorithm developed by EPRI, has been carried out in order to evaluate the performance of an OLM system. The results demonstrated that the OLM system was able to detect the drift of an instrument in the majority of the studied cases. A feasibility study has also been completed and has demonstrated that the implementation of an OLM system at a CANDU nuclear power plant could be advantageous under certain conditions.
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How this classification was reachedexpand
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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".