A new autoregressive moving average modeling of H/V spectral ratios to estimate the ground resonance frequency

Abstract

We propose a new method to estimate the horizontal-to-vertical (H/V) spectral ratio using microtremor measurements. The technique is based on modeling the H/V transfer function by means of an AutoRegressive Moving Average (ARMA) filter. As compared with the conventional, Fourier-based spectra processing routines, this method is efficient in extracting the fundamental resonant frequency with a higher spectral resolution. We demonstrate its usefulness by an application to several sites in northeastern Iberian Peninsula. For the data sets examined, our approach shows improvement over the Fourier transform-based method under adverse experimental conditions. We conclude that the new technique provides robust estimates of the fundamental resonance frequency and can be effective to characterize empirically the unconsolidated sediment thickness and bedrock geometry.

Subfluvial Tunnel Layout Design: Mapping Recent Sediment Fill in Bilbao Estuary Using H/V Spectral Ratio

“…However, a visual inspection of the transfer functions and the coherence associated with the peaks is necessary for validation. A variety of examples of peak validation are presented in Ugalde et al (2021). In this work, the spectral peaks obtained at sites B021 and B022…”

“…H/V analysis can be performed in combination with traditional geotechnical and geophysical methods to determine some geotechnical parameters (depth to bedrock and shear wave velocities) of shallow layers (e.g., Ibs-von Seht and Wohlenberg, 1999;García-Jerez et al, 2007;Gosar and Lenart, 2010;Rosenblad and Goetz, 2010;Tian et al, 2019;Assaf et al, 2022). The non-invasive technique is particularly useful in urban areas and has been applied, as in the present study, to estimate the thickness of alluvial sediment layers in Lisbon (Teves-Costa et al, 1996); Boston, Massachusetts (Yilar et al, 2017); and Nice, France (Rohmer et al, 2020), among others, Recently, Ugalde et al (2021) proposed a novel parametric spectral method to estimate the H/V spectral ratio of ambient vibration recordings based on modelling the H/V time series through an AutoRegressive Moving Average (ARMA) filter. This technique is robust and provides the natural frequency of the ground with higher spectral resolution than the classical methods based on the Fourier Transform.…”

Intelligent Prediction of Aeroengine Wear Based on the SVR Optimized by GMPSO

“…In order to verify the accuracy and consistency of the GMSO-SVR prediction method proposed in this paper, it was compared with the commonly used back propagation (BP) network [21] and auto regressive moving average (ARMA) [22]. Because the weights of the BP network are initialized randomly, the BP network performs calculations several times, and the best result was used for the comparison.…”

Horizontal-to-Vertical Spectral Ratio of Ambient Vibration Obtained with Hilbert–Huang Transform

“…The Horizontal-to-Vertical Spectral Ratio (HVSR) of ground motion measurements is a common tool to characterize near surface shear wave (Vs) structure [ 1 , 2 , 3 , 4 ]. It is often applied for earthquake risk assessments [ 5 , 6 ] and civil engineering [ 7 , 8 ].…”