Evidence map›Paper›PMID 38894159›Full record

ArticleSensors (Basel, Switzerland)2024

Yoke-Type Elasto-Magnetic Sensor-Based Tension Force Monitoring Method for Enhancement of Field Applicability.

Ho-Jun Lee, Sae-Byeok Kyung, Ju-Won Kim

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.

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0citing papers in PubMed
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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

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Ho-Jun LeeDepartment of Nuclear · Energy System Engineering, Graduate School, Dongguk University, Gyeongju 38066, Republic of Korea.ORCID 0009-0004-5593-6022
Sae-Byeok KyungDepartment of Nuclear · Energy System Engineering, Graduate School, Dongguk University, Gyeongju 38066, Republic of Korea.ORCID 0009-0008-6853-2034
Ju-Won KimDepartment of Safety Engineering, Dongguk University WISE, Gyeongju 38066, Republic of Korea.ORCID 0000-0001-5491-7103

Funding

Korea Hydro & Nuclear Power Co. and local government (Gyeongju) K-2022-A0296-00004Ministry of Trade, Industry and Energy, and the Korea Energy Technology Evaluation Institute (KETEP) 20214000 00001;National Research Foundation of Korea government (Ministry of Science and ICT) 2022R1C1C1007123
6 · The paper itself

Abstract

Tension members are key members that maintain stability and improve the strength of structures such as cable-stayed bridges, PSC structures, and slopes. Their application has recently been expanded to new fields such as mooring lines in subsea structures and aerospace fields. However, the tensile strength of the tension members can be abnormal owing to various risk factors that may lead to the collapse of the entire structure. Therefore, continuous tension monitoring is necessary to ensure structural safety. In this study, an improved elasto-magnetic (E/M) sensor was used to monitor tension force using a nondestructive method. General E/M sensors have limitations that make it difficult to apply them to operating tension members owing to their solenoid structure, which requires field winding. To overcome this problem, the magnetization part of the E/M sensor was improved to a yoke-type sensor, which was used in this study. For the development of the sensors, the numerical design and magnetization performance verification of the sensor were performed through eddy current solution-type simulations using ANSYS Maxwell. Using the manufactured yoke-type E/M sensor, the induced voltage signals according to the tension force of the specimen increasing from 0 to 10 tons at 1-ton intervals were repeatedly measured using DAQ with wireless communication. The measured signals were indexed using peak-to-peak value of induced voltages and used to analyze the signal change patterns as the tension increased. Finally, the analyzed results were compared with those of a solenoid-type E/M sensor to confirm the same pattern. Therefore, it was confirmed that the tension force of a tension member can be estimated using the proposed yoke-type E/M sensor. This is expected to become an effective tension monitoring technology through performance optimization and usability verification studies for each target tension member in the future.

Indexed as

linear regression analysistension force monitoringwireless communicationyoke-type elasto-magnetic sensor

Identifiers

PMID38894159
PMCPMC11174642

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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.