Fast Inversion of Air-Coupled Spectral Analysis of Surface Wave (SASW) Using in situ Particle Displacement

Spectral Analysis of Surface Wave (SASW) is widely used in nondestructive subsurface profiling for geological sites. The air-coupled SASW is an extension from conventional SASW methods by replacing ground-mounted accelerometers with non-contact microphones, which acquire a leaky surface wave instead...

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Bibliographic Details
Main Authors: Yifeng Lu, Yinghong Cao, J. Gregory McDaniel, Ming L. Wang
Format: Article
Language:English
Published: MDPI AG 2015-11-01
Series:ISPRS International Journal of Geo-Information
Subjects:
Online Access:http://www.mdpi.com/2220-9964/4/4/2619
Description
Summary:Spectral Analysis of Surface Wave (SASW) is widely used in nondestructive subsurface profiling for geological sites. The air-coupled SASW is an extension from conventional SASW methods by replacing ground-mounted accelerometers with non-contact microphones, which acquire a leaky surface wave instead of ground vibration. The air-coupled SASW is a good candidate for fast inspection in shallow geological studies. Especially for pavement maintenance, minimum traffic interference might be induced. One issue that restrains SASW from fast inspection is the traditional slow inversion which relies on guess-and-check iteration techniques including a forward analysis. In this article, a fast inversion analysis algorithm is proposed to estimate the shear velocity profile without performing conventional forward simulation. By investigating the attenuation of particle displacement along penetrating depths, a weighted combination relationship is derived to connect the dispersion curve with the shear velocity profile directly. Using this relationship, the shear velocity profile could be estimated from a given/measured dispersion curve. The proposed procedure allows the surface wave-based method to be fully automatic and even operated in real-time for geological site and pavement assessment. The method is verified by the forward analysis with stiffness matrix method. It is also proved by comparing with other published results using various inversion methods.
ISSN:2220-9964