Evidence map›Paper›PMID 31323846›Full record

ArticleSensors (Basel, Switzerland)2019

Comprehensive Improvement of the Sensitivity and Detectability of a Large-Aperture Electromagnetic Wear Particle Detector.

Ran Jia, Biao Ma, Changsong Zheng, Xin Ba, Liyong Wang, Qiu Du, Kai Wang

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.3field-weighted citation impact, top 11% of its field
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

7 citing papers in PubMed, 37 citations in OpenAlex.

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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 at 3 institutions in 2 countries.

Ran JiaSchool of Mechanical Engineering, Beijing Institute of Technology, Zhongguancun South Street No.5 Haidian District, Beijing 100081, China.ORCID 0000-0002-8430-4073
Biao MaSchool of Mechanical Engineering, Beijing Institute of Technology, Zhongguancun South Street No.5 Haidian District, Beijing 100081, China.
Changsong ZhengSchool of Mechanical Engineering, Beijing Institute of Technology, Zhongguancun South Street No.5 Haidian District, Beijing 100081, China. zhengchangsong@bit.edu.cn.
Xin BaSchool of Mechanical Engineering, Beijing Institute of Technology, Zhongguancun South Street No.5 Haidian District, Beijing 100081, China.
Liyong WangThe Ministry of Education Key Laboratory of Modern Measurement and Control Technology, Beijing Information Science and Technology University, Xiaoying East Street No.12, Beijing 100192, China.
Qiu DuSchool of Mechanical Engineering, Beijing Institute of Technology, Zhongguancun South Street No.5 Haidian District, Beijing 100081, China.
Kai WangSchool of Mechanical Engineering, Beijing Institute of Technology, Zhongguancun South Street No.5 Haidian District, Beijing 100081, China.
Beijing Institute of Technology · CNBeijing Information Science & Technology University · CNUniversity of Technology Sydney · AU

Funding

Beijing finance found of science and technology planning project KZ201611232032National Natural Science Foundation of China 51475044
6 · The paper itself

Abstract

The electromagnetic wear particle detector has been widely studied due to its prospective applications in various fields. In order to meet the requirements of the high-precision wear particle detector, a comprehensive method of improving the sensitivity and detectability of the sensor is proposed. Based on the nature of the sensor, parallel resonant exciting coils are used to increase the impedance change of the exciting circuit caused by particles, and the serial resonant topology structure and an amorphous core are applied to the inductive coil, which improves the magnetic flux change of the inductive coil and enlarges the induced electromotive force of the sensor. Moreover, the influences of the resonance frequency on the sensitivity and effective particle detection range of the sensor are studied, which forms the basis for optimizing the frequency of the magnetic field within the sensor. For further improving the detectability of micro-particles and the real-time monitoring ability of the sensor, a simple and quick extraction method for the particle signal, based on a modified lock-in amplifier and empirical mode decomposition and reverse reconstruction (EMD-RRC), is proposed, which can effectively extract the particle signal from the raw signal with low signal-to-noise ratio (SNR). The simulation and experimental results show that the proposed methods improve the sensitivity of the sensor by more than six times.

Indexed as

amorphous coreparticle detectionresonancesensitivitysignal extraction

Identifiers

PMID31323846
PMCPMC6679293
OpenAlexW2961767810

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.