Feedforward Piezoelectric Structural Control: An Application to Aircraft Cabin Noise Reduction
Bibliographic record
Abstract
The use of adaptive feedforward control within the active structural acoustic control framework was applied to the problem of propeller-induced noise and vibration reduction in the passenger cabin of the Bombardier (de Havilland) Dash-8 aircraft. Piezoceramic elements were used for structural actuation, and either vibration or acoustic sensing was employed. Actuators comprised of segmented piezoelectric elements were designed with the objective of reducing the noise and vibration levels at the propeller blade passage frequency (BPF) and the e rst harmonic.Theactuatordesignobjectivewassuppressionoftheoperating dee ectionshapes (ODS)ofthefuselageat the various frequencies by the judicious placement of piezoelectric elements. Using an actuator and sensor design optimized for the BPF together with vibration error sensing, the controller was successful in reducing interior noise in addition to vibration. Further improvement in noise reduction was obtained when acoustic error sensing was employed. Similar optimized designs for actuator and sensors were also found to exist at other frequencies, providing good noise and vibration attenuation. Furthermore, this strategy was successfully applied to noise reduction at two operating frequencies, where suppression of the ODSs at both the BPF and 2 £ BPF was the objective.
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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 | 0.000 | 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) | 0.001 | 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".