Diagnosis and Protection of IPM Motors Using Wavelet Packet Transform
Bibliographic record
Abstract
This paper presents the practical implementation of a new algorithm for the detection and diagnosis of stator electrical faults in three-phase interior permanent magnet (IPM) motors. Motor current signature analysis is performed off-line on the collected data to extract the most significant features from the fault currents. It has been found that magnitudes of harmonics for motor fault currents can be used to discriminate between different faulted and normal unfaulted conditions. The proposed algorithm utilized the multiresolution property of the WPT, and is based on the identification of fault harmonics using the selected mother wavelet `db3'. The novel wavelet packet transform (WPT) based algorithm for the protection of IPM motors is implemented and tested on-line on the laboratory 1-hp and 5-hp IPM motors. The single phasing fault, single line to ground (L-G) fault and line-to-line (L-L) fault are investigated. In all the tests carried out, the faults are detected, and the trip signal is initiated almost at the instant or within one cycle of the fault occurrence
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".