Evidence map›Paper›PMID 31546595›Full record

ArticleSensors (Basel, Switzerland)2019

Measurement of Three-Dimensional Structural Displacement Using a Hybrid Inertial Vision-Based System.

Xinxiang Zhang, Yasha Zeinali, Brett A Story, Dinesh Rajan

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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.

Xinxiang ZhangDepartment of Electrical and Computer Engineering, Southern Methodist University, Dallas, TX 75205, USA. xinxiang@mail.smu.edu.ORCID 0000-0002-9749-3336
Yasha ZeinaliDepartment of Civil and Environmental Engineering, Southern Methodist University, Dallas, TX 75205, USA. yhajizeinali@mail.smu.edu.
Brett A StoryDepartment of Civil and Environmental Engineering, Southern Methodist University, Dallas, TX 75205, USA. bstory@lyle.smu.edu.ORCID 0000-0002-9851-7790
Dinesh RajanDepartment of Electrical and Computer Engineering, Southern Methodist University, Dallas, TX 75205, USA. rajand@lyle.smu.edu.ORCID 0000-0001-9871-0681

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accurate three-dimensional displacement measurements of bridges and other structures have received significant attention in recent years. The main challenges of such measurements include the cost and the need for a scalable array of instrumentation. This paper presents a novel Hybrid Inertial Vision-Based Displacement Measurement (HIVBDM) system that can measure three-dimensional structural displacements by using a monocular charge-coupled device (CCD) camera, a stationary calibration target, and an attached tilt sensor. The HIVBDM system does not require the camera to be stationary during the measurements, while the camera movements, i.e., rotations and translations, during the measurement process are compensated by using a stationary calibration target in the field of view (FOV) of the camera. An attached tilt sensor is further used to refine the camera movement compensation, and better infers the global three-dimensional structural displacements. This HIVBDM system is evaluated on both short-term and long-term synthetic static structural displacements, which are conducted in an indoor simulated experimental environment. In the experiments, at a 9.75 m operating distance between the monitoring camera and the structure that is being monitored, the proposed HIVBDM system achieves an average of 1.440 mm Root Mean Square Error (RMSE) on the in-plane structural translations and an average of 2.904 mm RMSE on the out-of-plane structural translations.

Indexed as

camera calibrationcamera movement compensationmotion sensorout-of-planestatic structural displacement measurementstructural health monitoringthree-dimensionalvision-based

Identifiers

PMID31546595
PMCPMC6806297

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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.