Application of Hilbert-Huang transform to characterize soil liquefaction and quay wall seismic responses modeled in centrifuge shaking-table tests

et al. 2013

Nat Hazards

The Guantan landslide, with a total displaced mass of about 468 9 10 4 m 3 , was triggered by the 2008 Wenchuan earthquake and succeeding rainfall in Jushui Town, Sichuan Province, China. The landslide occurred on an anti-dip hard rock slope with a weak rock founding stratum of 200 m in thickness. To investigate the failure mechanism of the Guantan landslide, dynamic behaviors of hard and soft rock slopes were investigated by means of large scale shaking table tests. The laboratory models attempted to simulate the field geological conditions of the Guantan landslide. Sinusoidal waves and actual seismic waves measured from the Wenchuan Earthquake were applied on the slope models under 37 loading configurations. The experimental results indicated that deformation mainly developed at a shallow depth in the upper part of the hard rock slope and in the upper (near the crest) and lower (near the toe) parts of the soft rock slope. An equation for predicting the depth of sliding plane was proposed based on the location of the maximum horizontal acceleration. Finally, it was concluded that the failure process of the Guantan landslide occurred in three stages: (1) toppling failure caused by compression of the underlying soft rock strata, (2) formation of crushed hard rock and sliding surface in soft rock as the result of seismic shocks, particularly in the horizontal direction, and (3) aftershock rainfall accelerates the process of mass movement along the sliding plane.

Section: Shaking Table Testmentioning

confidence: 99%

Analysis of an anti-dip landslide triggered by the 2008 Wenchuan earthquake in China

Huang

et al. 2013

Nat Hazards

“…Results indicate the high correlation of the new seismic parameters with the damage indices and confirm that HHT is a promising tool for extracting information to characterize seismic damage in structures. The HHT was successfully used by Wei et al [131] to characterize the seismic responses of soil-quay wall systems using measured data in a series of geotechnical centrifuge shaking-table tests. It was found that the predominant instantaneous frequency at any given instant provides a superior indicator for characterizing the occurrence of liquefaction and the time-varying soil dynamic property.…”

Section: Seismic Effectmentioning

confidence: 99%

Application of Hilbert‐Huang Transform in Structural Health Monitoring: A State‐of‐the‐Art Review

Chen

Mathematical Problems in Engineering

2014

This paper reviews the development and application of HHT in the field of SHM in the last two decades. The challenges and future trends in the development of HHT based techniques for the SHM of civil engineering structures are also put forward. It also reviews the basic principle of the HHT method, which contains the extraction of the intrinsic mode function (IMF), mechanism of the EMD, and the features of HT; shows the application of HHT in the system identification, which contains the introduction of theoretical method, the identification of modal parameters, and the system identification on real structures; and discusses the structural damage detection using HHT based approaches, which includes the detection of common damage events, sudden damage events, and cracks and flaws.

“…However, that is usually not the case. Therefore, it is necessary to repeat the above sifting [27]. Treat ℎ 1 ( ) as a proto-IMF and define…”

Section: Empirical Mode Decomposition (Emd)mentioning

confidence: 99%

Short-Term Wind Speed Forecasting Using Decomposition-Based Neural Networks Combining Abnormal Detection Method

Chen

Abstract and Applied Analysis

et al. 2014

As one of the most promising renewable resources in electricity generation, wind energy is acknowledged for its significant environmental contributions and economic competitiveness. Because wind fluctuates with strong variation, it is quite difficult to describe the characteristics of wind or to estimate the power output that will be injected into the grid. In particular, shortterm wind speed forecasting, an essential support for the regulatory actions and short-term load dispatching planning during the operation of wind farms, is currently regarded as one of the most difficult problems to be solved. This paper contributes to short-term wind speed forecasting by developing two three-stage hybrid approaches; both are combinations of the five-three-Hanning (53H) weighted average smoothing method, ensemble empirical mode decomposition (EEMD) algorithm, and nonlinear autoregressive (NAR) neural networks. The chosen datasets are ten-minute wind speed observations, including twelve samples, and our simulation indicates that the proposed methods perform much better than the traditional ones when addressing short-term wind speed forecasting problems.