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Record W2905490444 · doi:10.1109/andescon.2018.8564677

Impact of Voltage Waveform on the Losses and Performance of Energy Efficiency Induction Motors

2018· article· en· W2905490444 on OpenAlexaff
Pablo D. Donolo, M. Pezzani, Guillermo R. Bossio, Enrique C. Quispe, Diego F. Valencia

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsMcMaster University
Fundersnot available
KeywordsInduction motorWaveformVoltageControl theory (sociology)Efficient energy useTotal harmonic distortionDistortion (music)Margin (machine learning)Energy consumptionHarmonic analysisEngineeringComputer scienceElectrical engineeringElectronic engineering

Abstract

fetched live from OpenAlex

This paper analyzes the effects of voltage harmonic distortion on the losses and efficiency of energy efficient induction motors (EEIM). Preliminary studies show that when fed with distorted voltages the new EEIM have a greater impact on efficiency than standard induction motors. Therefore, in this work a more precise steady state equivalent circuit is used to quantify accurately the impact of the distorted voltage waveform on losses and efficiency of induction motor. The model is validated using two induction motors both of 5.5kW, 50Hz, four poles; one is class IE3 Premium efficiency and the other is class lE1 standard efficiency. The analysis of the results may lead to infer that the EEIM are a good alternative to reduce energy consumption, but the margin is lower under fed with distorted voltages compared with ideal supply conditions.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.530
Threshold uncertainty score0.131

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.008
GPT teacher head0.205
Teacher spread0.197 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations7
Published2018
Admission routes1
Has abstractyes

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