A seven-sensor configuration method for testing thermal error of a horizontal machining center with linear optical grating scale
Bibliographic record
Abstract
A precision testing method based on a seven-sensor configuration is presented in this paper to quantify thermal errors (drifting, elongation, tilting) of the mandrel cross-section, for an example horizontal machining center with linear optical grating scale. Three tri-axial displacement sensors with 120° spread angles and 36 thermal couples are mounted on judiciously chosen locations to record the temperatures and thermal expansions for various operating conditions. Based on the measurements covering a wide range of spindle locations, environment temperatures, coolant temperature, and spindle rotational speeds, we found that (i) the maximum thermal drifts of the mandrel are 11.3 µm in the x direction with a compensation rate of 62%, and 165.3 µm in the y direction with a compensation rate of 93%, (ii) the maximum thermal tilt of the mandrel is 0.005°, and (iii) the thermal elongation of the mandrel in the z direction, which could not be compensated by the linear optical grating scale, is 51.9 µm. From a correlation study, the thermal elongation of the mandrel is most closely correlated to the temperatures recorded for the thermal couple mounted at the front surface of the spindle bearing with a correlation coefficient of 0.83.
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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 | 0.002 | 0.002 |
| 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 | 0.001 |
| Open science | 0.001 | 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".