Evidence map›Paper›PMID 35590956›Full record

ArticleSensors (Basel, Switzerland)2022

Panoramic/Dual-Surface Digital Image Correlation Measurement Using a Single Camera.

Kaiyu Zhu, Bing Pan

Open access · goldAbstract 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
1.1field-weighted citation impact, top 22% of its field
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, 11 citations in OpenAlex.

  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

2 authors at 1 institution in 1 country.

Kaiyu ZhuInstitute of Solid Mechanics, School of Aeronautic Science and Engineering, Beihang University, Beijing 100191, China.
Bing PanInstitute of Solid Mechanics, School of Aeronautic Science and Engineering, Beihang University, Beijing 100191, China.
Beihang University · CN

Funding

National Key Research and Development Program of China 2018YFB0703500National Natural Science Foundation of China 11872009National Natural Science Foundation of China 11925202National Science and Technology Major Project J2019-V-0006-0099
6 · The paper itself

Abstract

We propose a cost-effective and simple-to-implement mirror-assisted single-camera panoramic digital image correlation (DIC) method for panoramic/dual-surface profile and deformation measurement. Specifically, two planar mirrors and a single camera attached with a four-mirror adapter are used to capture stereo images of the front and rear surfaces of a test object. These stereo images can be processed by regular stereo-DIC to retrieve shape and kinematics fields of each surface. Further, with the speckle patterns prefabricated on the mirrors, reflection transformation matrices are obtained and applied to transform all reconstructed surfaces into a common world coordinate system. As such, panoramic/dual-surface shape and deformation measurements can be realized. For validation, a high-resolution smartphone camera and an industrial camera were, respectively, used to construct mirror-assisted single-camera panoramic DIC systems. Real experiments, including panoramic shape measurement of an aluminum cylinder, dual-surface shape measurement of an aluminum plate and uniaxial tensile tests of aluminum sheet specimens, were performed, confirming the feasibility and accuracy of the method. Since only a single camera and a few auxiliary reflective mirrors are required, the proposed method provides a cost-effective and convenient way for taking panoramic/dual-surface shape and deformation measurements of regular-sized cylindrical and bar samples.

Indexed as

digital image correlationexperimental mechanicspanoramic measurement

Identifiers

PMID35590956
PMCPMC9104215
OpenAlexW4224310018

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.