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Record W2160529147 · doi:10.1109/ccece.2006.277478

A Peak Detector for Multi-Rate Phase Locked Loop and Sequence Detector Combination for Utility AC Power Applications

2006· article· en· W2160529147 on OpenAlexafffund
Hamid Timorabadi, E. Chen, F.P. Dawson

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsUniversity of Toronto
FundersCMC Microsystems
KeywordsFast Fourier transformDetectorPhase detectorPhase-locked loopComputer scienceAmplitudeEstimatorSynchronization (alternating current)Electronic engineeringPhase synchronizationControl theory (sociology)Phase detector characteristicAlgorithmPhase noiseEngineeringElectrical engineeringPhysicsMathematicsVoltageTelecommunicationsOptics

Abstract

fetched live from OpenAlex

Synchronization is of concern in AC power systems. Existing synchronization algorithms are hardware intensive. A single phase synchronization scheme referred to as a multi-rate phase locked loop (MPLL) has been reported. The stability of the MPLL is influenced by amplitude variations. An amplitude estimation module based on a fast Fourier transform (FFT) algorithm and an automatic gain control (AGC) are employed to decouple amplitude variations from phase variations. The implementation of the FFT-based amplitude-estimator is complex and hardware intensive. A peak detector module that utilizes only two multiplexers and one comparator is proposed to replace the FFT-based amplitude-estimator. A real-time positive sequence detector is also combined with the MPLL in order to allow process of the three-phase signals. The overall system is implemented and compared for both FFT-based and peak detector approaches and indicates a 60 dB immunity to impulse noise and harmonic contamination and a 20 dB dynamic range

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 score0.943
Threshold uncertainty score0.626

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 head0.032
GPT teacher head0.288
Teacher spread0.256 · 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

Citations1
Published2006
Admission routes2
Has abstractyes

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