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Record W2081371460 · doi:10.1109/tie.2013.2288207

A Single-Switch Valley-Fill Power-Factor-Corrected Electronic Ballast for Compact Fluorescent Lightings With Improved Lamp Current Crest Factor

2013· article· en· W2081371460 on OpenAlexaff
John Lam, Shangzhi Pan, Praveen Jain

Bibliographic record

VenueIEEE Transactions on Industrial Electronics · 2013
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsQueen's University
Fundersnot available
KeywordsCrest factorBallastIncandescent light bulbPower factorFluorescent lampElectrical engineeringDuty cycleEngineeringPower (physics)Electronic circuitCurrent (fluid)Electronic engineeringVoltageComputer sciencePhysics

Abstract

fetched live from OpenAlex

Although compact fluorescent lamps (CFLs) have been on the market for a long time, many of them do not achieve the same power factor as the incandescent lamps do, which presents a significant problem for the utility with the current widespread use of CFLs for household lightings. A simple single-switch electronic ballast with passive valley-fill power factor correction is proposed in this paper for CFL application. The proposed single-switch ballast circuit is able to achieve zero current switching to maximize the circuit efficiency. A simple feedback circuit with duty ratio control is also proposed to improve the high lamp current crest factor caused by the valley-fill circuit. Detailed descriptions and analysis of the circuit operating principles are provided in this paper. Simulation and experimental results are given on a 13-W CFL tube from Osram Sylvania to highlight the merits of the proposed work.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.018
GPT teacher head0.218
Teacher spread0.199 · 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 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

Citations23
Published2013
Admission routes1
Has abstractyes

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