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Record W2522620389 · doi:10.1002/mop.30189

Backscattering technique for real‐time monitoring of the received power in wireless power transmission systems

2016· article· en· W2522620389 on OpenAlexaff
Telnaz Zarifi, Kambiz Moez, Pedram Mousavi

Bibliographic record

VenueMicrowave and Optical Technology Letters · 2016
Typearticle
Languageen
FieldEngineering
TopicWireless Power Transfer Systems
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsTransmitterElectrical engineeringSIGNAL (programming language)Impedance matchingTransmission (telecommunications)Rectifier (neural networks)Electronic engineeringInput impedanceVoltageEngineeringElectrical impedanceComputer scienceChannel (broadcasting)

Abstract

fetched live from OpenAlex

ABSTRACT A wireless power transmission system with a dynamic, real‐time feedback for impedance matching is presented. The AC signal at the receiver node is rectified, the resulting DC signal is passed to a voltage controlled oscillator which drives a high‐frequency analog switch. When in the ON state, the switch shorts the terminals of the receiver coil, dramatically changing the impedance seen by the transmitter coil. This change is detected on the transmitter side as the backscattered signal. Variation on the frequency of the backscattered signal can then be used to affect changes in the power source amplitude or the transmission side matching network to optimize the transmission power efficiency. The proposed feedback system is implemented with planar spiral coils on PCBs, and the effect of distance variation between the coils and as a consequence, DC voltage variation on the rectifier output is measured using voltage signal spectrum in the transmitter node at 1 MHz. © 2016 Wiley Periodicals, Inc. Microwave Opt Technol Lett 58:2980–2983, 2016

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.110
Threshold uncertainty score0.596

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 head0.006
GPT teacher head0.197
Teacher spread0.192 · 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 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

Citations1
Published2016
Admission routes1
Has abstractyes

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