Coupling effects of manufacturing error and flexible ring gear rim on dynamic features of planetary gear
Bibliographic record
Abstract
Manufacturing errors widely exist in and deteriorate the dynamic property of planetary gear train (PGT). To solve this problem, the ring gear is often designed with a thin rim to compensate for the effects of manufacturing errors via the elastic deflections of the rim. Existing dynamic models of the PGT only consider the effects of either the elasticity of the rim of the ring gear or the manufacturing errors. The coupling effects of manufacturing errors and the flexible ring gear are ignored. To understand the dynamic behaviors of the PGT better, a dynamic model of the PGT coupled with typical manufacturing error and flexible ring gear is developed in this study. The tooth contact analysis of the ring-planet mesh, which is calculated based on the potential energy method and uniformly curved Timoshenko beam theory, is studied using the influence coefficient method. A numerical algorithm is proposed to solve the integrated dynamic equations of the PGT. Calculated results show that the dynamic features of the PGT are complex, and the load sharing characteristic is improved when the flexible ring gear is incorporated.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".