Identification of aeroelastic parameters for helicopter tail rotor limit cycle oscillation monitoring
Bibliographic record
Abstract
The aeroelastic parameters of helicopter main rotor and tail rotor are required in the monitoring and evaluation of rotor aeroservoelastic instability incidents such as limit cycle oscillations. However, in situ measurement of these parameters on helicopters is generally difficult due to the need to transfer vibration data across a rotating interface. This article presents a novel center frequency scaling factor relationship of the aeroelastic parameters between the rotating and stationary frames. Together with the stochastic parameter identification technique, this methodology enables real-time estimation and tracking of the critical aeroelastic parameters in the rotating frame during limit cycle oscillation events based on vibration information measured exclusively in the stationary frame. The methodology has been validated using flight vibration data measured from both the rotating and stationary frames of a helicopter tail rotor system during a limit cycle oscillation event. Moreover, this methodology has been applied to the analysis of vibration data measured from the teeter tail rotor system on the Canadian CH-149 Cormorant helicopters to derive the critical aeroelastic parameters during several limit cycle oscillation events.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".