Evidence map›Paper›PMID 37447711›Full record

ArticleSensors (Basel, Switzerland)2023

A Vectorial Current Density Imaging Method Based on Magnetic Gradient Tensor.

Yangjing Wu, Mingji Zhang, Chengyuan Peng, Zehuang Zhang, Yichen He, Wenwei Zhang, Liang Chang

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Yangjing WuSino-German College of Intelligent Manufacturing, Shenzhen Technology University, Shenzhen 518118, China.ORCID 0009-0001-7036-4294
Mingji ZhangSino-German College of Intelligent Manufacturing, Shenzhen Technology University, Shenzhen 518118, China.
Chengyuan PengSino-German College of Intelligent Manufacturing, Shenzhen Technology University, Shenzhen 518118, China.
Zehuang ZhangSino-German College of Intelligent Manufacturing, Shenzhen Technology University, Shenzhen 518118, China.ORCID 0009-0001-2051-8080
Yichen HeSino-German College of Intelligent Manufacturing, Shenzhen Technology University, Shenzhen 518118, China.
Wenwei ZhangSino-German College of Intelligent Manufacturing, Shenzhen Technology University, Shenzhen 518118, China.
Liang ChangState Grid Liaoning Electric Power Co., Ltd., Huludao 125000, China.

Funding

Guangdong Regular Universities Special Fund for Major Areas 2022ZDZX3022, 2022GCZX005National Natural Science Foundation of China 61901271Natural Science Foundation of Guangdong Province Science and Technology Program of Shenzhen JCYJ20200109115403807Special Project of Self-Made Experimental Instruments and Equipment in Shenzhen Technology University JSZZ202201016The Postgraduate Innovation Development Fund Project of Shenzhen University 20213108010007
6 · The paper itself

Abstract

Magnetic current imaging is deemed an emerging powerful technique for visualizing electrical currents in electronic devices. However, the existing magnetic-field-based Fourier Transform back-evolution method is limited by its mono-function of imaging the magnitude of current density in devices under test, and subject to background noise distortion. Here, we developed a novel vectorial current density imaging method based on the detection of the magnetic field gradient generated by current carrying conductors. A closed form solution of current density inversion was analytically derived and numerically verified. Experiments were conducted by scanning tri-axial fluxgate sensor over different shapes of electrical wires. The results show that a current density resolution of 24.15 mA/mm

Indexed as

Magnetic Resonance ImagingMagneticsFourier AnalysisMagnetic FieldsPhantoms, Imagingclosed-form inversioncurrent density inversionmagnetic current imagingmagnetic gradient tensornondestructive testing

Identifiers

PMID37447711
PMCPMC10346920

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.