A Novel Precision-characterization Model of a Revolute Joint Based on the Concept of Spatial Mechanisms with Redundant Elastic Constraints
Bibliographic record
Abstract
摘要： 提出回转副精度特性的弹性冗余空间机构模型，将实际回转副中的弹性约束等效映射为多个从动件弹性冗余支承，实际回转副零件的几何误差特性等效映射为刚性凸轮轮廓曲面，形成以多组从动件弹性悬浮刚性凸轮几何轮廓的弹性冗余空间机构，从而较真实地反映实际回转副结构及其零件的几何、运动、材料物理性质与工况载荷特性等因素的耦合关系。建立弹性冗余空间凸轮机构的几何位移基本方程、静力平衡方程、物性方程，将回转副精度及其随位置和载荷变化的特性转化为弹性冗余空间机构的位移分析与静力分析求解问题，并给出典型回转副精度特性计算分析与试验测试对比示例，为机器精度分析与设计提供新的理论基础，也为机构学理论开辟新的应用领域。
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.006 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".