Synchronous Generator Off-line Diagnosis Approach Including Fault Detection and Estimation of Failures on Machine Parameters
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Bibliographic record
Abstract
Abstract Fault diagnosis involves the detection, location, and identification of faults. The objective of this work is twofold: first, fault detection in a synchronous generator using the parity space approach, a method based on building the fault indicators using analytical redundancy relationships, a generator model, and actual input and output data; second, computation of defaulting synchronous generator parameters using the maximum likelihood estimation algorithm, which combines the generalized least-squares estimator, the linear Kalman filter, and the Newton-type finite-difference optimization algorithm. In the first step, the proposed technique is successfully applied for external faults diagnosis of two generators: (1) a 4-pole, 60-Hz, 208-V, 1.5-kVA loaded laboratory synchronous generator using a 3-phase, sudden short-circuit fault at 10% rated voltage, and (2) an unloaded 20-pole, 60-Hz, 13.2-kV, 13.75-MVA large generator at Hydro-Québec's Rapides-des-Quinzes plant following a scenario of a 10% line-to-line short-circuit fault. For external faults, failures on parameters do not exist. The proposed scheme could therefore aid in building an automatic protective relay for the synchronous generators. In the second step, the diagnosis process is applied for the fault detection and determination of failures on parameters occurring on the 1.5-kVA generator following broken damper rotor's bars using finite-element simulated data.
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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 | 0.000 |
| 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 it