Evidence map›Paper›PMID 34770632›Full record

ArticleSensors (Basel, Switzerland)2021

Study of Building Safety Monitoring by Using Cost-Effective MEMS Accelerometers for Rapid After-Earthquake Assessment with Missing Data.

Jian-Fu Lin, Xue-Yan Li, Junfang Wang, Li-Xin Wang, Xing-Xing Hu, Jun-Xiang Liu

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
3.9field-weighted citation impact, top 6% 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 41 citations in OpenAlex.

  1. Pooled it
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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

6 authors at 3 institutions in 1 country.

Jian-Fu LinCenter of Safety Monitoring of Engineering Structures, Shenzhen Academy of Disaster Prevention and Reduction, China Earthquake Administration, Shenzhen 518003, China.
Xue-Yan LiMOE Key Laboratory of Disaster Forecast and Control in Engineering, School of Mechanics and Building Engineering, Jinan University, Guangzhou 510632, China.ORCID 0000-0003-1339-8145
Junfang WangMOE Key Laboratory for Resilient Infrastructures of Coastal Cities, College of Civil and Transportation Engineering, Shenzhen University, Shenzhen 518060, China.
Li-Xin WangCenter of Safety Monitoring of Engineering Structures, Shenzhen Academy of Disaster Prevention and Reduction, China Earthquake Administration, Shenzhen 518003, China.
Xing-Xing HuInstitute of Geophysics, China Earthquake Administration, Beijing 100081, China.
Jun-Xiang LiuCenter of Safety Monitoring of Engineering Structures, Shenzhen Academy of Disaster Prevention and Reduction, China Earthquake Administration, Shenzhen 518003, China.
China Earthquake Administration · CNJinan University · CNShenzhen University · CN

Funding

China Earthquake Administration's Science for Earthquake Resilience Project XH204702Guangdong Provincial Key R& D Program 2019B111106001Guangdong Provincial Science and Technology Plan Project 2018B020207011National Key R&D Program of China 2019YFB2102700 and 2019YFC1511005-05Shenzhen Key Laboratory of Structure Safety and Health Monitoring of Marine Infrastructures (In Preparation) ZDSYS20201020162400001
6 · The paper itself

Abstract

Suffering from structural deterioration and natural disasters, the resilience of civil structures in the face of extreme loadings inevitably drops, which may lead to catastrophic structural failure and presents great threats to public safety. Earthquake-induced extreme loading is one of the major reasons behind the structural failure of buildings. However, many buildings in earthquake-prone areas of China lack safety monitoring, and prevalent structural health monitoring systems are generally very expensive and complicated for extensive applications. To facilitate cost-effective building-safety monitoring, this study investigates a method using cost-effective MEMS accelerometers for buildings' rapid after-earthquake assessment. First, a parameter analysis of a cost-effective MEMS sensor is conducted to confirm its suitability for building-safety monitoring. Second, different from the existing investigations that tend to use a simplified building model or small-scaled frame structure excited by strong motions in laboratories, this study selects an in-service public building located in a typical earthquake-prone area after an analysis of earthquake risk in China. The building is instrumented with the selected cost-effective MEMS accelerometers, characterized by a low noise level and the capability to capture low-frequency small-amplitude dynamic responses. Furthermore, a rapid after-earthquake assessment scheme is proposed, which systematically includes fast missing data reconstruction, displacement response estimation based on an acceleration response integral, and safety assessment based on the maximum displacement and maximum inter-story drift ratio. Finally, the proposed method is successfully applied to a building-safety assessment by using earthquake-induced building responses suffering from missing data. This study is conducive to the extensive engineering application of MEMS-based cost-effective building monitoring and rapid after-earthquake assessment.

Indexed as

EarthquakesMicro-Electrical-Mechanical SystemsAccelerationAccelerometryCost-Benefit Analysisafter-earthquake assessmentbuilding safety monitoringcost-effective MEMS accelerometermissing data reconstructionstructural health monitoring

Identifiers

PMID34770632
PMCPMC8587995
OpenAlexW3208547876

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.