Development of Fault Diagnosis and Failure Prediction Techniques for Small Gas Turbine Engines
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A computer model of a gas turbine auxiliary power unit was produced to develop techniques for fault diagnosis and prediction of remaining life in small gas turbine engines. Due to the relatively low capital cost of small engines it is important that the techniques have both low capital and operating costs. Failing engine components were identified with fault maps, and an algorithm was developed for predicting the time to failure, based on the engine’s past operation. Simulating daily engine operation over a maintenance cycle tested the techniques for identification and prediction. The simulation included daily variations in ambient conditions, operating time, load, engine speed and operating environment, to determine the amount of degradation per day. The algorithm successfully adapted to the daily changes and corrected the operating point back to standard conditions to predict the time to failure.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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