Condition Monitoring of Wind Turbines: A Case Study of the Gibara II Wind Farm
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
The main objective of this study is to investigate the adaptation of wind turbines at the Gibara II Wind Farm in Cuba, which operates in a tropical climate that differs from the typical conditions in which these turbines are designed and manufactured in the northern hemisphere.The study utilizes condition monitoring techniques supported by Big Data acquired through a supervisory control and data acquisition (SCADA) system.By statistically processing normalized databases using multiple linear regression equations, the study establishes mathematical models that characterize the behavior of critical variables such as bearing, oil and winding temperatures, electrical generation, and specific climatic conditions unique to the wind farm under analysis.These models are essential for advancing condition-based maintenance (CBM) practices and developing preventive measures to mitigate functional failures.The significance of this research lies in the historical technical performance of the equipment under investigation, highlighting the importance of addressing the challenges posed by different environmental conditions.The study was conducted using the relevant regulatory technical documentation pertaining to the design of the wind turbines at the Gibara II Wind Farm.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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