Inversion Model of GPR Imaging Characteristics of Point Objects and Fracture Detection of Heritage Building

Joint Authors

Yang, Jie
Hu, De-xiu
Li, Ning
Yao, Xianchun
Lv, Gao
Pang, Rixuan

Source

Journal of Sensors

Issue

Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-10, 10 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2018-05-07

Country of Publication

Egypt

No. of Pages

10

Main Subjects

Civil Engineering

Abstract EN

There are often many hidden structural defects in heritage buildings.

As a convenient and effective nondestructive detecting method, ground-penetrating radar (GPR) has a technical advantage in detecting and protecting heritage buildings depending on the advanced image interpretation.

The analytic relationship between buried depth and radius of point object and long and short axis of hyperbolic equation was established according to derivations of formulas.

The image characteristics of hyperbolic curves with different depth and radius were studied by finite-difference time-domain method (FDTD).

And then, inversion models of buried depth and radius of point object were established.

The buried depth and radius can be accurately deduced by long and short axis of hyperbolic image.

This result was applied in the detection of pedestal defects of the heritage building, and the depth and distribution range of hidden fracture can be accurately interpreted.

It provides an effective and fast method to detect hidden defects in civil engineering.

American Psychological Association (APA)

Lv, Gao& Li, Ning& Yang, Jie& Yao, Xianchun& Hu, De-xiu& Pang, Rixuan. 2018. Inversion Model of GPR Imaging Characteristics of Point Objects and Fracture Detection of Heritage Building. Journal of Sensors،Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1201046

Modern Language Association (MLA)

Lv, Gao…[et al.]. Inversion Model of GPR Imaging Characteristics of Point Objects and Fracture Detection of Heritage Building. Journal of Sensors No. 2018 (2018), pp.1-10.
https://search.emarefa.net/detail/BIM-1201046

American Medical Association (AMA)

Lv, Gao& Li, Ning& Yang, Jie& Yao, Xianchun& Hu, De-xiu& Pang, Rixuan. Inversion Model of GPR Imaging Characteristics of Point Objects and Fracture Detection of Heritage Building. Journal of Sensors. 2018. Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1201046

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1201046