A review of Ground Penetrating Radar application in civil engineering: A 30-year journey from Locating and Testing to Imaging and Diagnosis-Reference-Cited by-同舟云学术

A review of Ground Penetrating Radar application in civil engineering: A 30-year journey from Locating and Testing to Imaging and Diagnosis

Published:2018-06 Issue: Volume:96 Page:58-78
ISSN:0963-8695
Container-title:NDT & E International
language:en
Short-container-title:NDT & E International

Author:

Wai-Lok Lai Wallace,Dérobert Xavier,Annan Peter

Publisher

Elsevier BV

Subject

Mechanical Engineering,Condensed Matter Physics,General Materials Science

Reference289 articles.

1. Commission FC FCC Part 15–Radio Frequency Devices, Code of Federal Regulation 47 CFR Ch. 1 (10-1-). Section.

2. RSS-220-Devices Using UltraWideband (UWB) Technology. Spectrum Management and Telecommunications Radio Standards Specification: Industry Canada; 2009.

3. ETSI EN 301 489–32. Electromagnetic compatibility and Radio spectrum Matters (ERM); Electromagnetic Compatibility (EMC) standard for radio equipment and services; Part 32: Specific conditions for Ground and Wall Probing Radar applications;. 2006.

4. Debye PJW. Polar Molecules: Chemical Catalog Company, Incorporated; 1929.

5. Dispersion and absorption in dielectrics I. Alternating current characteristics;Cole;J Chem Phys,1941

Cited by 361 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Enhancing subsurface exploration: A comprehensive review of advanced clutter removal techniques for ground penetrating radar imaging;Measurement;2025-01

2. REN-GAN: Generative adversarial network-driven rebar clutter elimination network in GPR image for tunnel defect identification;Expert Systems with Applications;2024-12

3. A digital workflow for assessing lifespan, carbonation, and embodied carbon of reusing concrete in buildings;Journal of Building Engineering;2024-11

4. Characterization of leakage signatures in buried water pipes by ground penetrating radar(GPR) and instantaneous frequency analysis;Tunnelling and Underground Space Technology;2024-11

5. Compressive strength detection of tunnel lining using hyperspectral images and machine learning;Tunnelling and Underground Space Technology;2024-11