Evidence map›Paper›PMID 35591219›Full record

ArticleSensors (Basel, Switzerland)2022

Theoretical and Experimental Studies of Micro-Surface Crack Detections Based on BOTDA.

Baolong Yuan, Yu Ying, Maurizio Morgese, Farhad Ansari

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

4 authors.

Baolong YuanCollege of Information and Control Engineering, Shenyang Jianzhu University, Shenyang 110168, China.
Yu YingCollege of Information and Control Engineering, Shenyang Jianzhu University, Shenyang 110168, China.ORCID 0000-0002-2639-1877
Maurizio MorgeseDepartment of Civil and Materials Engineering, University of Illinois at Chicago, 842 W Taylor St., Chicago, IL 60607, USA.ORCID 0000-0003-2441-2854
Farhad AnsariDepartment of Civil and Materials Engineering, University of Illinois at Chicago, 842 W Taylor St., Chicago, IL 60607, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Micro-surface crack detection is important for the health monitoring of civil structures. The present literature review shows that micro-surface cracks can be detected by the Brillouin scattering process in optical fibers. However, the existing reports focus on experiment research. The comparison between theory and experiment for Brillouin-scattering-based optical sensors is rarely reported. In this paper, a distributed optical fiber sensor for monitoring micro-surface cracks is presented and demonstrated. In the simulation, by using finite element methods, an assemblage of a three-dimensional beam model for Brillouin optical time domain analysis (BOTDA) was built. The change in Brillouin frequency (distributed strain) as a function of different cracks was numerically investigated. Simulation results indicate that the amplitudes of the Brillouin peak increase from 27 με to 140 με when the crack opening displacement (COD) is enlarged from 0.002 mm to 0.009 mm. The experiment program was designed to evaluate the cracks in a beam with the length of 15 m. Experimental results indicate that it is possible to detect the COD in the length of 0.002~0.009 mm, which is consistent with the simulation data. The limitations of the proposed sensing method are discussed, and the future research direction is prospected.

Indexed as

Brillouin frequencydistributed optical fiber sensormicro-cracks

Identifiers

PMID35591219
PMCPMC9105900

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.