Modification and nonlinear dynamics characteristics analysis of herringbone gears based on coupling of meshing force and stiffness
Bibliographic record
Abstract
Gear modification is an important technology for the design and manufacturing of high-precision gear transmissions, which is an effective method to improve gear meshing performance, reduce vibration, and noise. This paper employs the coordinate transformation method to calculate the meshing angle of herringbone gear, which simplifies the calculation of the relative displacement of the meshing line. Also, considering the influence of dynamic meshing force at the meshing point of gear pairs on time-varying meshing stiffness, an improved nonlinear dynamic model was established, and a novel internal excitation real-time correction method was proposed to predict the system’s dynamic characteristics more accurately. Next, the effects of different modification methods, modification amounts, and damping ratios on the nonlinear dynamic characteristics of the herringbone gear pair were analyzed. The obtained results show that the average relative displacement of the meshing line increases with the increase of the amount of modification. Moreover, its standard deviation decreases with the increase of the modification in some rotating speed ranges. In some cases, it can even be reduced by more than 50%. When the damping ratio decreases gradually, the axial modification can shorten the chaos interval by 52.68%, but the periodic window will disappear after modification.
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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 | 0.001 |
| 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".