Evidence map›Paper›PMID 41516495›Full record

ReviewSensors (Basel, Switzerland)2025

Toward Active Distributed Fiber-Optic Sensing: A Review of Distributed Fiber-Optic Photoacoustic Non-Destructive Testing Technology.

Yuliang Wu, Xuelei Fu, Jiapu Li, Xin Gui, Jinxing Qiu, Zhengying Li

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2025. 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. Nondestructive Inspection of Water Pipes: A Review.Sensors (Basel, Switzerland) · 2026
    Review
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

6 authors.

Yuliang WuSchool of Information Engineering, Wuhan University of Technology, Wuhan 430062, China.ORCID 0000-0002-8161-990X
Xuelei FuSchool of Information Engineering, Wuhan University of Technology, Wuhan 430062, China.ORCID 0000-0002-4962-3773
Jiapu LiSchool of Information Engineering, Wuhan University of Technology, Wuhan 430062, China.
Xin GuiNational Engineering Research Center of Fiber Optic Sensing Technology and Networks, Wuhan University of Technology, Wuhan 430062, China.ORCID 0000-0002-3640-6278
Jinxing QiuSchool of Information Engineering, Wuhan University of Technology, Wuhan 430062, China.
Zhengying LiSchool of Information Engineering, Wuhan University of Technology, Wuhan 430062, China.ORCID 0000-0002-4600-2795

Funding

National Natural Science Foundation of China 52205574National Natural Science Foundation of China 62575224National Natural Science Foundation of China U24A20306
6 · The paper itself

Abstract

Distributed fiber-optic photoacoustic non-destructive testing (DFP-NDT) represents a paradigm shift from passive sensing to active probing, fundamentally transforming structural health monitoring through integrated fiber-based ultrasonic generation and detection capabilities. This review systematically examines DFP-NDT's evolution by following the technology's natural progression from fundamental principles to practical implementations. Unlike conventional approaches that require external excitation mechanisms, DFP-NDT leverages photoacoustic transducers as integrated active components where fiber-optical devices themselves generate and detect ultrasonic waves. Central to this technology are photoacoustic materials engineered to maximize conversion efficiency-from carbon nanotube-polymer composites achieving 2.74 × 10

Indexed as

distributed fiber-optic photoacoustic transducer arrayfiber-optic ultrasonic sensingnon-destructive testingphotoacoustic materialsstructural health monitoring

Identifiers

PMID41516495
PMCPMC12787691

What OpenQuestion holds

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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.