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Record W2767342346 · doi:10.1109/ias.2017.8101730

The wavelet modulation technique for 1φ CHB multi-level DC-AC power electronic converters

2017· article· en· W2767342346 on OpenAlexaff
S. A. Saleh

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsWaveletConvertersPulse-width modulationModulation (music)HarmonicsWaveformElectronic engineeringPower (physics)Wavelet transformComputer scienceVoltageControl theory (sociology)EngineeringPhysicsElectrical engineeringArtificial intelligenceAcoustics

Abstract

fetched live from OpenAlex

This paper presents the development and performance evaluation of the wavelet modulation technique for single phase (1φ) cascaded ff-bridge (CHB) multi-level dc-ac power electronic converters (PECs). The developed technique is based on employing sets of resolution-segmented wavelet basis functions as switching signals, where each set operates one ff-bridge. The number of sets of wavelet basis functions is selected to match the number of levels in the output voltage of the 1φ CHB dc-ac PEC. The wavelet modulation for 1φ CHB multi-level dc-ac PECs is implemented for performance evaluation both in simulation and experimentation. The performance of the developed technique is evaluated for linear, nonlinear, and dynamic loads. Simulation results show significant reduction of output harmonics, along with high magnitude of the fundamental component ion the output voltage. The improvements offered by the wavelet modulation technique are further demonstrated through comparisons with the level-shifted and phase-shifted pulse-width modulation techniques under similar loading 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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.989
Threshold uncertainty score0.669

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 studies0.0010.000
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 head0.031
GPT teacher head0.257
Teacher spread0.226 · 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 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

Citations2
Published2017
Admission routes1
Has abstractyes

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