Separation of the vibration-induced signal of oil debris for vibration monitoring
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Oil debris sensors are designed for monitoring machine component conditions by detecting oil debris in the circulating oil lines. However, these sensors are not only sensitive to metallic particles, but are susceptible to machinery vibration as well. The vibration-induced signal has thus far been treated as interference and is accordingly removed to better reveal the particle signature. As the vibration signal also contains important information on machine health, which can be used to detect not only the machine component faults but also machine structural malfunctions, we propose a joint integral and wavelet transform approach to separate the vibration and particle signals to make the oil debris sensor multi-functional. The recovered vibration signal is then used to detect faults that cannot be revealed by examining oil debris content. Our experimental results have shown that the separated vibration signal is, in general, consistent with the vibration velocity and hence can be used as an auxiliary vibration monitoring tool.
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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 it