Drivetrain Noise Source Identification and Active Noise Control of a Heavy Off-Road Vehicle
Bibliographic record
Abstract
<div class="section abstract"><div class="htmlview paragraph">Drivetrain noise from heavy off-road vehicles mainly includes engine noise, drive shaft noise, wheel-side gear noise, tire pattern noise etc. They are the main noise sources for such vehicles as they greatly influence the ride comfort of the passengers inside. This paper solved the drivetrain noise problems of a heavy off-road vehicle using the method of active noise control (ANC). Firstly, the vehicle is benchmarked and the noise problems are analyzed, while the noise sources are identified by analyzing the transmission principles of the drivetrain. Secondly, ANC strategies are made for the vehicle based on the noise profiles under various operating conditions. Thirdly, the multiple parameters for ANC are computed from simulations modeling the vehicle in idle, constant speed and acceleration respectively. Lastly, road tests are conducted using the multiple parameters from the simulations and a noise reduction of 2-4 dB can be achieved in the whole vehicle. The results has shown that ANC is an effective method for drivetrain noise reduction in heavy off-road vehicles as this paper provides references for the systematic solution dealing with such problem.</div></div>
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How this classification was reachedexpand
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".