Evidence map›Paper›PMID 29443920›Full record

ArticleSensors (Basel, Switzerland)2018

Gradient-Type Magnetoelectric Current Sensor with Strong Multisource Noise Suppression.

Mingji Zhang, Siu Wing Or

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Magnetoelectric Sensor Operating inSensors (Basel, Switzerland) · 2024
    Article
  3. Article
  4. Article
  5. Article
  6. Self-Biased Bidomain LiNbOSensors (Basel, Switzerland) · 2020
    Article
  7. Article
  8. Article
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

2 authors.

Mingji ZhangDepartment of Electrical Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China. mingji.zhang@connect.polyu.hk.ORCID 0000-0001-9531-5862
Siu Wing OrDepartment of Electrical Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China. eeswor@polyu.edu.hk.ORCID 0000-0003-2536-5658

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A novel gradient-type magnetoelectric (ME) current sensor operating in magnetic field gradient (MFG) detection and conversion mode is developed based on a pair of ME composites that have a back-to-back capacitor configuration under a baseline separation and a magnetic biasing in an electrically-shielded and mechanically-enclosed housing. The physics behind the current sensing process is the product effect of the current-induced MFG effect associated with vortex magnetic fields of current-carrying cables (i.e., MFG detection) and the MFG-induced ME effect in the ME composite pair (i.e., MFG conversion). The sensor output voltage is directly obtained from the gradient ME voltage of the ME composite pair and is calibrated against cable current to give the current sensitivity. The current sensing performance of the sensor is evaluated, both theoretically and experimentally, under multisource noises of electric fields, magnetic fields, vibrations, and thermals. The sensor combines the merits of small nonlinearity in the current-induced MFG effect with those of high sensitivity and high common-mode noise rejection rate in the MFG-induced ME effect to achieve a high current sensitivity of 0.65-12.55 mV/A in the frequency range of 10 Hz-170 kHz, a small input-output nonlinearity of <500 ppm, a small thermal drift of <0.2%/℃ in the current range of 0-20 A, and a high common-mode noise rejection rate of 17-28 dB from multisource noises.

Indexed as

current sensormagnetic field gradientmagnetoelectric effectmultisource noise suppression

Identifiers

PMID29443920
PMCPMC5855880

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.