To ensure the safe operation of roads, it is necessary to periodically monitor the condition of road surfaces. Lately, near-surface geophysics methods have been actively used to solve such problems. The seismoacoustic methods that are used to diagnose road surfaces are typically dynamic methods based on the excitation of body or surface elastic waves in the road surfaces. The purpose of this work is to assess the possibilities of using elastic standing waves for diagnosing a hard road surface. This article presents the results of field experiments that demonstrate the possibility of detecting cavities under an asphalt pavement using flexural standing waves. Such waves, like vibrations of a membrane fixed or partially fixed at its edges, can be formed on the hard surface cover above the cavity as a result of exposure to acoustic noise. In this article, the accumulation of amplitude spectra of a large number of noise records was used to extract standing waves from the acoustic noise recorded on the surface of the pavement. It is shown that the joint visualization of the averaged spectra obtained by profile observations over the cavity makes it possible to confidently identify several modes of flexural standing waves. Based on the areal measurements, a map of the distribution of the amplitudes of one of the modes of flexural standing waves in the asphalt pavement over the cavity was constructed. At a qualitative level, this distribution is consistent with the results of computer simulations using the finite element method. The fact that, under the influence of acoustic noise in the pavement, the flexural standing waves are formed which are absent at other places indicates the absence of rigid contact at its lower boundary. Thus, the horizontal dimensions of the cavity can be estimated from the size of the area on which flexural standing waves are formed. In addition, the article shows that the analysis of vertical compressional (but not flexural) standing waves arising in the pavement under the influence of noise allows us to investigate the thickness of the pavement and to qualitatively assess the ratio of acoustic stiffness of the pavement and the underlying layer.
