A Comparison of Several SDOF Models of Gear Dynamics
Bibliographic record
Abstract
It is commonly believed that a complete understanding of gear dynamics is essential for the design of gear transmission systems capable of running at low noise and vibration levels with prolonged service life. Several single degree of freedom (SDOF) models of gear dynamics with clearance nonlinearity are generalized based on previous research, while a constant damping ratio is assumed and the friction is neglected. These models include the effects of time-varying mesh stiffness, gear manufacturing errors, profile modifications and backlash. Comparisons of the steady responses predicted by these SDOF models are intensively studied and the relationships between these models are discussed. Even though, different types of mesh stiffness and different treatments of the gear error functions in the analysis are used in these models, the steady-state responses predicted by these models are generally consistent with each other and agree well with experimental results. However, some discrepancies and relationships do exist among these models. The advantages and disadvantages of each model are highlighted.
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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) | 0.000 | 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) | 0.000 | 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".