Evidence map›Paper›PMID 31936696›Full record

ArticleSensors (Basel, Switzerland)2020

Bridge Damage Identification Using Vehicle Bump Based on Additional Virtual Masses.

Qingxia Zhang, Jilin Hou, Łukasz Jankowski

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. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 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

3 authors.

Qingxia ZhangSchool of Civil Engineering, Dalian Minzu University, Dalian 116600, China.
Jilin HouDepartment of Civil Engineering & State Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian 116023, China.ORCID 0000-0002-3554-7036
Łukasz JankowskiInstitute of Fundamental Technological Research, Polish Academy of Sciences, 02-106 Warsaw, Poland.ORCID 0000-0002-9773-0688

Funding

Liaoning Provincial Natural Science Foundation of China 20180551205National Key Research and Development Program of China 2018YFC0705604National Natural Science Foundation of China (NSFC) 51878118National Science Centre, Poland DEC- 2017/25/B/ST8/01800
6 · The paper itself

Abstract

Structural damage identification plays an important role in providing effective evidence for the health monitoring of bridges in service. Due to the limitations of measurement points and lack of valid structural response data, the accurate identification of structural damage, especially for large-scale structures, remains difficult. Based on additional virtual mass, this paper presents a damage identification method for bridges using a vehicle bump as the excitation. First, general equations of virtual modifications, including virtual mass, stiffness, and damping, are derived. A theoretical method for damage identification, which is based on additional virtual mass, is formulated. The vehicle bump is analyzed, and the bump-induced excitation is estimated via a detailed analysis in four periods: separation, free-fall, contact, and coupled vibrations. The precise estimation of bump-induced excitation is then applied to a bridge. This allows the additional virtual mass method to be used, which requires knowledge of the excitations and acceleration responses in order to construct the frequency responses of a virtual structure with an additional virtual mass. Via this method, a virtual mass with substantially more weight than a typical vehicle is added to the bridge, which provides a sufficient amount of modal information for accurate damage identification while avoiding the bridge overloading problem. A numerical example of a two-span continuous beam is used to verify the proposed method, where the damage can be identified even with 15% Gaussian random noise pollution using a 1-degree of freedom (DOF) car model and 4-DOF model.

Indexed as

additional virtual massbridgedamage identificationstructural health monitoringvehicle bump

Identifiers

PMID31936696
PMCPMC7013881

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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.