Contrôle actif du bruit et des vibrations de la transmission principale d'un Bell 407
Bibliographic record
Abstract
The main objective of this research project is to study the feasibility and effectiveness of active structural acoustic control of the main transmission of a Bell 407 under laboratory conditions. Ultimately this project should lead to a reduction of the level of noise inside the passenger area of this helicopter. This project is a collaborative program between Bell Helicopter Textron Canada Limited, the Consortium for Research and Innovation in Aerospace in Quebec (CRIAQ) and the Groupe d'Acoustique de l'Université de Sherbrooke (GAUS). The first step was the characterization of the source of noise and vibration with vibroacoustic spectra from ground and flight tests on a Bell 407. The tones associated to the transmission in the 500 Hz to 3000 Hz range were identified. Secondly, a laboratory setup was developed. Essentially, this laboratory setup is a simplified representation of the main transmission-roof-cabin system of the Bell 407. The laboratory setup was validated with various impact tests on a Bell 407. Then, a finite element model of the laboratory setup was developed under MSC.NASTRAN. This model was also experimentally validated. The finite element model of the laboratory setup was used to realize many optimal active control simulations. The objective of these simulations was to find a configuration of control actuators and error sensors effective to attenuate the mean square velocity of the receiving panel of the laboratory setup. Finally, the laboratory setup was used for the laboratory demonstration of active control. The most effective configuration obtained from the simulations was experimentally implemented. Promising active control results were obtained with 2 different algorithms, the filtered-reference least mean square (FXLMS) and the principal component least mean square (PCLMS).
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".