Reliability based design of fluid power pitch systems for wind turbines
Why this work is in the frame
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Bibliographic record
Abstract
Abstract This paper presents a qualitative design tool for evaluation of the risk for fluid power pitch systems. The design tool is developed with special attention to industry standard failure analysis methods and is aimed at the early phase of system design. Firstly, the concept of Fault Tree Analysis is used for systematic description of fault propagation linking failure modes to system effects. The methodology is conducted solely on a circuit diagram and functional behavior. The Failure Mode and Effects Criticality Analysis is subsequently employed to determine the failure mode risk via the Risk Priority Number. The Failure Mode and Effect Criticality Analysis is based on past research concerning failure analysis of wind turbine drive trains. Guidelines are given to select the severity, occurrence and detection score that make up the risk priority number. The usability of the method is shown in a case study of a fluid power pitch system applied to wind turbines. The results show a good agreement to recent field failure data for offshore turbines where the dominating failure modes are related to valves, accumulators and leakage. The results are further used for making design improvements to lower the overall risk of the pitch system. Copyright © 2017 John Wiley & Sons, Ltd.
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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