Application of the Hilbert–Huang transform to identify the dynamic characteristics of a caisson foundation during liquefaction

Abstract

Summary This paper presents the application of a Hilbert–Huang transform data processing technique in a dynamic response analysis to identify the dynamic characteristics of a caisson foundation during liquefaction. The degradation of structural modal frequencies during liquefaction under strong earthquakes directly related to a reduction in the stiffness of the soil‐foundation structure due to the loss of strength, and the nonlinearity of the liquefied soil layer always occur in a short time. Thus, the short‐duration variation of frequencies provided a good indicator for the occurrence of the liquefaction and geometric distortion of a soil foundation system during strong earthquakes and was a very important step in the structural health monitoring work of foundation structures. This study shows that the proposed approach was effective in identifying the instantaneous downshift of frequency of caisson foundation system during liquefaction. This study was based on the measured acceleration response data of a test foundation model from a 1‐G shaking table test. Additionally, 2D numerical modeling using a total stress analysis stipulated in the highway bridge specification (JRA 2002), an equivalent linear method in the liquefaction calculation of foundation, was conducted to evaluate the consistency with vibration testing.

Detection of the instantaneous frequency degradation due to damages of a fixed offshore jacket platform using the iEEMD‐based Hilbert Huang transform under a wave excitation

“…Huang et al 10,16 developed a powerful technique named HHT in order to analyze both nonlinear and nonstationary signals. The HHT is a combination of EMD and Hilbert spectral analysis (HSA) as mentioned by Trung 17 . The EMD algorithm decomposes the signal into some intrinsic mode functions (IMFs).…”

“…The HHT is a combination of EMD and Hilbert spectral analysis (HSA) as mentioned by Trung. 17 The EMD algorithm decomposes the signal into some intrinsic mode functions (IMFs). However, one of the problems in EMD is that the mode mixing and the different frequency signals can exist in the same IMF as commented by Chang.…”

Novel vibration structural health monitoring technology for deep foundation piles by non‐stationary higher order frequency response function

“…A big number of literature sources related to vibration investigation of dynamic behavior of deep foundation piles exist with a particular focus on soil–pile interaction. However, vibration of piles is mostly a subject for researchers in order to investigate pile performance either during installation procedure or under a seismic loading rather than the purpose of assessment of pile integrity . Thus, the motivation of this paper is to develop a novel automatic vibration‐based diagnosis for the foundation piles at early stage of damage development.…”

Real‐time system identification using hierarchical interhealing model classes

“…The goal of system identification is to build a representative mathematical model for the underlying system based on the observed data and prior knowledge including assumptions, hypotheses, and paradigms. A number of system identification methods have been developed, for example, subspace identification 10,11 , substructural identification methods, 12–17 artificial neural networks, 18,19 Hilbert–Huang transform, 20,21 wavelet transform, 22–24 evolutionary strategy, 25,26 and the NEXT technique 27 .…”