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Record W2123232446 · doi:10.1109/ias.1996.560239

Nonlinear high-frequency switching filters for the DC-Side of AC/DC power converters

2002· article· en· W2123232446 on OpenAlexaff
D.A. Deib, J.M.S. Kim

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsHarmonicsConvertersPulse-width modulationSwitched-mode power supplyElectronic engineeringRectifier (neural networks)PWM rectifierComputer scienceControl theory (sociology)VoltageEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

In most of high power DC applications, phase-controlled rectifiers are still the preferred power converter because of their simplicity and reduced cost. However, the output voltage of a rectifier contains harmonics in addition to the desired DC voltage. This paper explains the concept of the nonlinear shunt- and series-type switching filters, using high-frequency switching PWM power converters. Two new circuits for DC-side switching filtering are developed and compared to the existing topologies. The design, modelling, control and principle of operation of the new DC-side switching filters are described. The salient features of the proposed fillers are the reduced filter power converter rating, reduced size of passive elements, and the elimination of the auxiliary power supply that has been used for series-type and shunt-type active filters. All analyses and control system designs are verified with simulation as well as experimental verification.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

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 communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.012
GPT teacher head0.210
Teacher spread0.198 · 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

Citations5
Published2002
Admission routes1
Has abstractyes

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