DEVELOPMENT OF AN EXPERIMENTAL TECHNIQUE TO MODEL DEFLECTIONS IN SURFACE GRINDING
Bibliographic record
Abstract
Deflections in surface grinding can lead to geometrical inaccuracies in the components being ground and can also limit production rates in the grinding process. This paper develops and tests an experimental technique to indirectly measure the deflections in the surface grinding process by comparing the actual mass removed during a grinding pass to the mass that would have been removed if there were no deflections. The relationships between the spindle power, normal force and grinding deflections are then derived. The experimental technique was applied to both a Brown & Sharpe 824 Micromaster conventional surface grinding machine, as well as a Blohm Planomat 408 CNC creep-feed grinding machine in the Grinding Research Laboratory at Dalhousie University. For the Brown & Sharpe surface grinder, the experimental results show a linear relationship between the spindle power and the grinding deflections, which agree well with the literature. For the Blohm Planomat grinding machine, however, the relationship between the spindle power and the deflections is nonlinear. Further investigation revealed that this nonlinearity is primarily due to the presence of backlash in the spindle lead screw.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".