Gearbox fault diagnosis via generalized velocity synchronous Fourier transform and order analysis
Bibliographic record
Abstract
Gearboxes have essential roles in many types of industrial equipment. Fault detection for gearboxes is important yet extremely difficult because volatile working conditions lead to nonstationary vibration signals. Order tracking is a classic and effective technique for nonstationary vibration analysis and fault diagnosis of rotating machinery. Many order tracking methods that do not require a tachometer have been proposed, such as methods based on re-sampling. However, most are complex and often introduce interpolation errors. To avoid such difficulties, a simple yet effective method is proposed in this paper. This method employs the generalized demodulation approach to extract a component with a frequency proportional to the instantaneous shaft rotational frequency from the vibration signal. Then, demodulating the extracted component recovers the instantaneous shaft rotational phase. With such information the order spectrum can be directly obtained via a velocity synchronous discrete Fourier transform. Finally, the fault can be diagnosed by order spectrum analysis. The effectiveness of this method is validated with both simulated and lab experimental vibration signals of a gearbox under time-varying rotational speed conditions.
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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 | 0.001 |
| 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) | 0.000 | 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".