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Record W2156171071 · doi:10.1109/ccece.1997.614784

A novel smart compensator for energy/power quality enhancement of nonlinear loads

2002· article· en· W2156171071 on OpenAlexaff
A.M. Sharaft, Chenxia Guo, Hongwei Huang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower Quality and Harmonics
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsPulse-width modulationRippleHarmonicsHarmonicModulation (music)Torque rippleNonlinear systemInrush currentPower (physics)Electronic engineeringControl theory (sociology)EngineeringComputer scienceInduction motorElectrical engineeringVoltageControl (management)PhysicsDirect torque control

Abstract

fetched live from OpenAlex

The paper presents a novel flexible smart compensator converter scheme for energy utilization enhancement and/or power quality harmonic ripple control. The converter topology is flexible and can be controlled by pulse width modulation (PWM), pulse frequency modulation (PFM) or a combined PWM/PFM switching strategy to ensure power quality enhancement and better energy utilization of nonlinear cyclical arc or inrush type electric loads. This includes large industrial induction motors, robotic drives, industrial arc-furnaces, and fluorescent industrial commercial lighting schemes.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.871
Threshold uncertainty score1.000

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)0.0010.000

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 head0.062
GPT teacher head0.274
Teacher spread0.212 · 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.

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

Citations1
Published2002
Admission routes1
Has abstractyes

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