Gpr Raw-Data Order Statistic Filtering and Split-Spectrum Processing To Detect Moisture

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Date

2014

Authors

Kilic, Gokhan

Journal Title

Journal ISSN

Volume Title

Publisher

Mdpi

Open Access Color

GOLD

Green Open Access

No

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Publicly Funded

No
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Average
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Average
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Average

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Abstract

Considerable research into the area of bridge health monitoring has been undertaken; however, information is still lacking on the effects of certain defects, such as moisture ingress, on the results of ground penetrating radar (GPR) surveying. In this paper, this issue will be addressed by examining the results of a GPR bridge survey, specifically the effect of moisture in the predicted position of the rebars. It was found that moisture ingress alters the radargram to indicate distortion or skewing of the steel reinforcements, when in fact destructive testing was able to confirm that no such distortion or skewing had occurred. Additionally, split-spectrum processing with order statistic filters was utilized to detect moisture ingress from the GPR raw data.

Description

Keywords

GPR and data processing, bridge structures, structures, non-destructive, moisture ingress, split-spectrum processing (SSP), order statistic filters, Ground-Penetrating Radar, Nondestructive Evaluation, Concrete, Inspection, Ndt, split-spectrum processing (SSP), moisture ingress, Science, Q, bridge structures, order statistic filters, GPR and data processing; bridge structures; structures; non-destructive; moisture ingress; split-spectrum processing (SSP); order statistic filters, non-destructive, GPR and data processing, structures

Fields of Science

0103 physical sciences, 01 natural sciences

Citation

WoS Q

Q1

Scopus Q

Q1
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OpenCitations Citation Count
3

Source

Remote Sensıng

Volume

6

Issue

6

Start Page

4687

End Page

4704
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Citations

CrossRef : 3

Scopus : 4

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Mendeley Readers : 26

SCOPUS™ Citations

4

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Web of Science™ Citations

4

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1

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Downloads

9

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OpenAlex FWCI
0.4862

Sustainable Development Goals

9

INDUSTRY, INNOVATION AND INFRASTRUCTURE
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