Acoustic Emission and Its Relationship with Friction and Wear for Sliding Contact
Bibliographic record
Abstract
Further investigation of the relationships between friction and wear properties and the characteristics of acoustic emission was conducted in the case of dry and grease-lubricated sliding contact using a ball-on-cylinder testing apparatus. The effect of contamination simulated by the inclusion of glass bead particles was also explored. Experiments were performed at sliding speeds ranging from 0.09 m/s to 1.47 m/s, while maintaining a fixed load and duration. As a first observation and contrary to what could be expected, the higher speed did not contribute to the decrease in friction interpreted by a worsening of the starved regime that had a consequence of increasing wear. However, the results revealed a good correlation between the friction coefficient and acoustic emission (AE) rms voltage for dry sliding. Such a relationship may allow the prediction of a reasonable friction coefficient μ from an AE signal. It was also determined that the friction work correlated well with the corresponding integrated AE voltage over time, intRMS. The detection of the sliding speed threshold beyond which accelerated wear would occur was possible from the intRMS variation. Proportionality between the theoretically determined grease film thickness and the intRMS was observed.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".