A Method of Interstory Drift Monitoring Using a Smartphone and a Laser Device.

Jinke Li, Botao Xie, Xuefeng Zhao

Abstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing 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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Jinke LiState Key Laboratory of Coastal and Offshore Engineering, School of Civil Engineering; Dalian University of Technology, Dalian 116024, China.ORCID 0000-0001-9454-4612

Botao XieState Key Laboratory of Coastal and Offshore Engineering, School of Civil Engineering; Dalian University of Technology, Dalian 116024, China.

Xuefeng ZhaoState Key Laboratory of Coastal and Offshore Engineering, School of Civil Engineering; Dalian University of Technology, Dalian 116024, China.

Funding

National Key R&D Program of China during the Thirteenth Five-Year Plan Period 2016YFC0802002National Key Research and Development Program 2016YFE0202400

6 · The paper itself

Abstract

Interstory drift is an important engineering parameter in building design and building structural health monitoring. However, many problems exist in current interstory drift monitoring methods. The traditional method is imprecise-double numerical integration of acceleration data-and other direct monitoring methods need professional equipment. This paper proposes a method to solve these problems by monitoring the interstory drift with a smartphone and a laser device. In this method, a laser device is installed on the ceiling while a smartphone is fixed on a steel projection plate on the floor. Compared with a reference sensor, the method designed in this study shows that a smartphone is competent in monitoring the interstory drift. This method utilizes a smartphone application (APP) named D-Viewer to implement monitoring and data storage just in one place, which is also inexpensive. The results showed that this method has an average percent error of 3.37%, with a standard deviation of 2.67%. With the popularization of the smartphone, this method is promising in acquiring large amounts of data, which will be significant for building assessment after an earthquake.

Indexed as

interstory driftlaser deviceseismic monitoringsmartphonestructural health monitoring

Identifiers

PMID32210147

DOI10.3390/s20061777

PMCPMC7147600

What OpenQuestion holds

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LicenceCC BY

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Registered trials

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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.