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Record W2168555392 · doi:10.1109/apec.1997.581443

Modeling and simulation of traveling waves in induction motor drives

2002· article· en· W2168555392 on OpenAlexaff
G. Joós

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Compatibility and Noise Suppression
Canadian institutionsConcordia University
Fundersnot available
KeywordsOvervoltageInduction motorInverterEmtpWaveformFilter (signal processing)Adjustable-speed driveVoltagePower (physics)Traveling waveModeling and simulationControl theory (sociology)Computer scienceEngineeringElectrical engineeringSimulationElectric power systemPhysics

Abstract

fetched live from OpenAlex

Adjustable speed induction motor drives are used more and more often in industry, particularly as an energy saving measure. In the standard configuration, the motor is fed from a voltage source inverter. A number of motor winding failures have been recorded and attributed to overvoltage resulting from the high dv/dt inverter outputs waveforms. This paper is a contribution to the modelling and simulation of the traveling wave phenomenon in induction motor drives. Modelling options for the feed cables are discussed and the use of distributed parameter modelling is proposed. The influence of line length and power semiconductor switching times on the magnitude of overvoltages are investigated. Simulation studies are carried out using the EMTP software package. Solutions are proposed and a filter design procedure is given. Selected results are verified experimentally.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.019
GPT teacher head0.220
Teacher spread0.202 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations18
Published2002
Admission routes1
Has abstractyes

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