Modeling of the Screw-Nut Interface Dynamics of Ballscrew Drives
Bibliographic record
Abstract
One aspect of ballscrew drives that requires a great deal of attention when modeling is the interface between the ballscrew and nut. This is because it plays an important role in the transmission of motion, vibrations and forces from the ballscrew to the table. Current models of the screw-nut interface consider only the axial and/or torsional deflections of the ballscrew while assuming that the lateral deformations of the ballscrew are decoupled from its torsional and axial deformations so cannot be transmitted through the screw-nut interface to the table. This paper however develops a model for the screw-nut interface that considers the lateral deformations of the ballscrew in addition to its axial and torsional deformations. The result of the modeling shows that, contrary to the aforementioned assumptions, the torsional, axial and lateral deformations of the ballscrew are coupled through the screw-nut interface. Therefore a torque applied to the ballscrew via the motor actually gives rise to lateral deformations on the ballscrew which could both affect its fatigue life and potentially the positioning accuracy of the ballscrew drive. These findings are verified by experiments on a single-axis ballscrew drive.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".