Inverted Tooth Chain Sprocket with Frequency-Modulated Meshing Features to Reduce Camshaft Drive Noise
Bibliographic record
Abstract
This paper outlines the design and development of an inverted tooth style sprocket that incorporates tooth profile features to reduce chain drive noise levels by modulating or “staggering” the chain-sprocket meshing impacts. Meshing frequency modulation was achieved by replacing a number of the standard teeth with a tooth form altered to include an offset engaging flank surface to vary the location and the rhythm of the meshing impacts. This altered tooth form was arrayed with the standard teeth in a random or arbitrary pattern in order to create a random meshing sprocket, thus serving to modulate the chain meshing impact frequency compared to that of a standard inverted tooth sprocket having a full complement of symmetrical teeth. Noise and vibration tests were conducted on a 4-cylinder DOHC non-firing “motored” engine in an anechoic test cell. The tests were done to compare the camshaft drive noise levels for a 24-tooth standard crankshaft sprocket with that of a new 24-tooth random meshing sprocket. The testing confirmed the N&V gains with the random meshing sprocket at meshing frequency (24th order) and the first harmonic (48th order) as well as for the overall chain drive noise levels.
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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 | 0.001 |
| 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".