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Record W2654940493 · doi:10.1049/iet-smt.2016.0325

Impedance matching network for ground eliminated open‐ended resonant coil structure in distributed wireless power transmission systems

2017· article· en· W2654940493 on OpenAlexafffund
Telnaz Zarifi, Kambiz Moez, Pedram Mousavi

Bibliographic record

VenueIET Science Measurement & Technology · 2017
Typearticle
Languageen
FieldEngineering
TopicWireless Power Transfer Systems
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaAlberta InnovatesNational Science CouncilAlberta Innovates - Technology Futures
KeywordsImpedance matchingElectrical impedanceElectromagnetic coilPower transmissionTransmission (telecommunications)Electrical engineeringElectronic engineeringMatching (statistics)WirelessComputer scienceElectric power transmissionPower (physics)AcousticsPhysicsTelecommunicationsEngineeringMathematics

Abstract

fetched live from OpenAlex

This study reports a novel technique utilising a standing‐wave node as a virtual ground to implement an impedance matching network and power level tuning in a ground eliminated (GE) open‐ended resonant coil structure. This technique with GE open‐ended coils can potentially be used in wireless power transmission (WPT) systems, where an unknown metallic, ungrounded, arbitrary environment is used as a signal propagation medium to deliver electric power to several distributed nodes. To satisfy WPT standards the proposed resonant WPT system with the matching network is implemented and tested at 13.56 MHz. A comprehensive study of the GE open‐ended resonant coil structure demonstrates ground‐plane effects and the necessity of an impedance matching network in no‐ground signal situations. The experimental results confirm the theoretical analysis presenting 9% improvements in mismatch efficiency, and 13.1 times in power transmission efficiency at 13.56 MHz when the matching network is deployed.

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)0.001
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.025
GPT teacher head0.263
Teacher spread0.237 · 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

Citations7
Published2017
Admission routes2
Has abstractyes

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