Evidence map›Paper›PMID 36363442›Full record

ReviewMaterials (Basel, Switzerland)2022

A Review of Radio Frequency Identification Sensing Systems for Structural Health Monitoring.

Muchao Zhang, Zhaoting Liu, Chuan Shen, Jianbo Wu, Aobo Zhao

Abstract readReview
In one paragraph

Review in Materials (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

5 authors.

Muchao ZhangSchool of Mechanical Engineering, Sichuan University, Chengdu 610065, China.ORCID 0000-0002-0241-2776
Zhaoting LiuSchool of Mechanical Engineering, Sichuan University, Chengdu 610065, China.
Chuan ShenSchool of Mechanical Engineering, Sichuan University, Chengdu 610065, China.
Jianbo WuSchool of Mechanical Engineering, Sichuan University, Chengdu 610065, China.ORCID 0000-0002-4732-6732
Aobo ZhaoNuclear Advanced Manufacturing Research Centre, iHub, Infinity Park Way, Derbyshire DE24 9FU, UK.ORCID 0000-0001-7272-441X

Funding

National Natural Science Foundation of China 92060114
6 · The paper itself

Abstract

Structural health monitoring (SHM) plays a critical role in ensuring the safety of large-scale structures during their operational lifespan, such as pipelines, railways and buildings. In the last few years, radio frequency identification (RFID) combined with sensors has attracted increasing interest in SHM for the advantages of being low cost, passive and maintenance-free. Numerous scientific papers have demonstrated the great potential of RFID sensing technology in SHM, e.g., RFID vibration and crack sensing systems. Although considerable progress has been made in RFID-based SHM, there are still numerous scientific challenges to be addressed, for example, multi-parameters detection and the low sampling rate of RFID sensing systems. This paper aims to promote the application of SHM based on RFID from laboratory testing or modelling to large-scale realistic structures. First, based on the analysis of the fundamentals of the RFID sensing system, various topologies that transform RFID into passive wireless sensors are analyzed with their working mechanism and novel applications in SHM. Then, the technical challenges and solutions are summarized based on the in-depth analysis. Lastly, future directions about printable flexible sensor tags and structural health prognostics are suggested. The detailed discussion will be instructive to promote the application of RFID in SHM.

Indexed as

applicationsbattery-lessradio frequency identificationsensor tagsstructural health monitoringstructural health prognostics

Identifiers

PMID36363442
PMCPMC9656519

What OpenQuestion holds

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LicenceCC BY
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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.