Evidence map›Paper›PMID 39000881›Full record

ArticleSensors (Basel, Switzerland)2024

Self-Sensing Electromechanical System Integrated with the Embedded Displacement Sensor.

Shuxian Wang, Shiyou Liu, Zuqiang Su, Linlin Liu, Zhi Tang

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. 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

5 authors.

Shuxian WangThe Institute of Advanced Manufacturing Engineering, Chongqing University of Posts and Telecommunictions, Chongqing 400065, China.ORCID 0000-0002-9786-1717
Shiyou LiuChongqing Qingshan Industry Co., Ltd., Chongqing 402761, China.
Zuqiang SuThe Institute of Advanced Manufacturing Engineering, Chongqing University of Posts and Telecommunictions, Chongqing 400065, China.
Linlin LiuThe Institute of Advanced Manufacturing Engineering, Chongqing University of Posts and Telecommunictions, Chongqing 400065, China.
Zhi TangThe Institute of Advanced Manufacturing Engineering, Chongqing University of Posts and Telecommunictions, Chongqing 400065, China.

Funding

Spectial support for Chongqing postdoctoral research project 2010010005361963The Chongqing University of University of Posts and Telecommunications research fund E012A2021210The Natural Science Foundation of China under Grant 52205553the Science and technology research project of Chongqing Education Commission KJQN202300628
6 · The paper itself

Abstract

Conventionally, the electromechanical system requires the installation of auxiliary displacement sensors and only the amount on the drive part and motion end, which increases volume, cost, and measurement error in the system. This paper presents an integrated measurement method with a sensing head, which takes the equal division characteristics of mechanical structures as part of the sensor, thus, the so-called self-sensing system. Moreover, the displacement is measured by counting the time pulses. The sensing head is integrated with the entire electromechanical system, including the driving, transmitting, and moving parts. Thus, the integration of the sensing part is greatly improved. Taking the rotary table as a special example, and the sensing head embedded into each part of the system, displacement information is obtained by the common processing system and fused by the adaptive weighted average method. The results of the experiment show that the fusion precision of each component is higher than only the motor position information as the feedback. The proposed method is a practical self-sensing technology with significant volume reduction and intelligent control benefits in the industry, especially suitable for extremely small and narrow spaces.

Indexed as

electromechanical systemembeddedintegrationposition detectionself-sensing

Identifiers

PMID39000881
PMCPMC11244118

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.