Diagnosis of Defected Rolling Bearings via Vibration Analysis Method
Bibliographic record
Abstract
The main function of rolling element bearings is to provide low friction conditions for supporting and guiding a rotating shaft. The rolling element bearing includes both ball bearings and roller bearings. Rolling element bearings operate with a rolling action whereas plain bearings operate with a sliding action. In various applications, these bearings are considered as critical mechanical components since defect in these components may lead to malfunction and catastrophic failure in some cases. Vibration analysis is one of the most established methods used to evaluate the condition of bearings in operating machines. In this paper, an abnormal detection structure, in which different types of abnormal detection routines can be applied, is proposed. Bearing fault modes and their effects on the bearing vibration are discussed. In order to achieve this purpose, a feature extraction method is developed to overcome the limitation of time domain features. Experimental data from bearings under different operating conditions are used to verify the proposed method.
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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 | 0.001 |
| 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 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".