Discrete Wavelet Transform Based Detection of Disturbances in Induction Motors
Bibliographic record
Abstract
In this work, two discrete wavelet transform (DWT) based algorithms, which have both a detection and classification phase, are developed for diagnosing and detecting various disturbances occurring in three-phase induction motors. In the first approach, the criterion for the detection phase is the comparison of the DWT coefficients of fault currents using the selected mother wavelet `db3' at the sixth level of resolution with a threshold determined experimentally during healthy condition of the motor. A feature vector representing the second norm of details of fault currents of six levels of resolution is used to discriminate between different faults. The second approach is based on the comparison of modulus maxima of the DWT coefficients for fault detection. The classification of faults is based on localized parameters estimation. The protection phase of both the algorithms is implemented in real-time using the ds1102 digital signal processor board. It gives a trip signal almost at the instant or within one cycle of the fault occurrence in all cases of faults
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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 | 0.000 | 0.001 |
| 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) | 0.000 | 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 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".