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Remote Sens. 2014, 6(6), 4687-4704; doi:10.3390/rs6064687

GPR Raw-Data Order Statistic Filtering and Split-Spectrum Processing to Detect Moisture

Department of Civil Engineering, Izmir University of Economics, Sakarya Cad. No:156, Balçova, 35330 Izmir, Turkey
Received: 31 January 2014 / Revised: 5 May 2014 / Accepted: 7 May 2014 / Published: 26 May 2014
(This article belongs to the Special Issue Close-Range Remote Sensing by Ground Penetrating Radar)
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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. View Full-Text
Keywords: GPR and data processing; bridge structures; structures; non-destructive; moisture ingress; split-spectrum processing (SSP); order statistic filters GPR and data processing; bridge structures; structures; non-destructive; moisture ingress; split-spectrum processing (SSP); order statistic filters
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Kilic, G. GPR Raw-Data Order Statistic Filtering and Split-Spectrum Processing to Detect Moisture. Remote Sens. 2014, 6, 4687-4704.

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