Development of an active suspension system for adaptive vibration control of helicopter seats
Bibliographic record
Abstract
The high level vibration of helicopter flight can cause physiological damage to the aircrew and may lead to occupational health issues. This paper presents the development of an active suspension system for helicopter seats to reduce the vibration levels transmitted to the aircrew body. Flight test on a Bell-412 helicopter was conducted to measure the aircrew body vibration levels and vibration transmission through the seat structures. In addition, an experimental modal analysis on a Bell-412 pilot seat equipped with a mannequin was carried out to investigate the seat and aircrew dynamics to identify critical vibration modes. Based on these tests, an active suspension system for the helicopter seat has been developed to be integrated on helicopter seats to reduce the vibration locally. This active suspension system included two stacked piezoelectric actuators installed on the seat frame as active struts to provide effective control authority to the critical mannequin vibration modes. A proof-of-concept active suspension system has been retrofitted on a full-scale Bell-412 pilot seat and the performance has been evaluated through extensive closed-loop control experiments performed on a mechanical shaker system. The mechanical shaker system was able to generate the representative vibration environment of the seat during flight. Test results demonstrated simultaneous suppression of the critical mannequin vibration modes and achieved significant global reduction of body vibration levels, which verified the effectiveness of the active suspension system for the helicopter seat to mitigate the vibration transmitted to the helicopter aircrew. The test results verified the effectiveness of an active suspension system implemented on the seat as a potential solution to reduce long term health issues faced by the helicopter aircrew.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".