Bibliographic record
Abstract
An output-only modal analysis (OMA) approach is presented to obtain the direct frequency response function (FRF) at the tip of the tool in micromilling setups. White noise input is provided using acoustic excitation and the resulting vibrations are measured using a laser Doppler vibrometer (LDV). Autoregressive (AR) identification is used to extract the natural frequencies and damping ratios of the structural modes of the milling setup, and mass-sensitivity analysis is used to obtain modal stiffness values. The accuracy of the tool tip FRFs that are constructed using OMA is verified by comparing them against the FRFs that are measured using impulse hammer tests. The direct FRF at the tool tip is an essential component in predicting and avoiding excessive and unstable vibrations in milling operations, and the presented approach provides a practical method for the direct measurement of the tool tip FRF in micromilling where the application of traditional hammer tests is not possible.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".