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

المؤلفون المشاركون

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

المصدر

Journal of Sensors

العدد

المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-10، 10ص.

الناشر

Hindawi Publishing Corporation

تاريخ النشر

2018-05-07

دولة النشر

مصر

عدد الصفحات

10

التخصصات الرئيسية

هندسة مدنية

الملخص 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.

نمط استشهاد جمعية علماء النفس الأمريكية (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

نمط استشهاد الجمعية الأمريكية للغات الحديثة (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

نمط استشهاد الجمعية الطبية الأمريكية (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

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-1201046