Real-time performance testing of a 3Φ VS WM inverter-fed induction motor
Bibliographic record
Abstract
This paper presents a real-time performance testing of a three-phase (3phi) voltage-source (VS) six-pulse wavelet-modulated (WM) inverter-fed induction motor (IM). The proposed modulation technique is based on a set of three scale-based linearly-combined scaling functions shifted by 2pideg/3 from each other. These scaling functions are employed to sample three reference-modulating signals, each corresponds to one phase, in a non-uniform recurrent manner. Moreover, these scaling functions have dual synthesis scaling functions that are responsible for reconstructing the three continuous-time (CT) reference- modulating signals from their non-uniform recurrent samples. The reconstruction processes are carried out by the three synthesis scaling functions to achieve 180-degrees conduction mode of the 3phi six-pulse inverter. The proposed wavelet modulation technique is realized through a Turbo - C code that is executed by a dSPACE dsl 102 DSP board to generate switching pulses to activate the inverter six IGBT switches. The IGBT inverter supplies a 1 hp, 1750 RPM, 208 V, 60 Hz, F-connected 3phi squirrel-cage induction motor that is tested for several speeds. These test results demonstrate robust performance, simple implementation, significant dynamic responses and high ability to maintain high quality outputs.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".