Artificial accelerograms composition based on the CEEMD

Vrochidou, Εleni; Alvanitopoulos, Petros-Fotios; Andreadis, Ioannis; Elenas, Anaxagoras

doi:10.1177/0142331216654533

Cited by 4 publications

(2 citation statements)

References 19 publications

(37 reference statements)

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“…Te empirical mode decomposition method can efectively divide the original vibration data into intrinsic mode sequences of diferent time scales. In this paper, the empirical mode decomposition method used was CEEMD [28], focusing on the analysis of the frst-and second-order intrinsic mode sequences and calculating the marginal spectrum [29]of the frst two-order intrinsic mode sequences. Taking as an example, the vibration data collected when the melting time of the frozen plane is 1 min, the time domain data are shown in Figure 5, and the marginal spectrum of the frst two eigenmode sequences of the bedrock mass and dangerous rock mass model vibration sequence is shown in Figure 6.…”

Section: Experimental Data Processing Methodmentioning

confidence: 99%

Experimental Study on the Vibration Characteristics of Dangerous Rock Mass under Constant Micromotion

Zhang

Xie

Huang

et al. 2023

Advances in Civil Engineering

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In mountainous areas, dangerous rock mass collapse is a serious threat to human life and property safety. However, how to effectively prevent and control the instability of dangerous rock mass is still an urgent unsolved problem. In this study, the dynamic characteristics of dangerous rock mass under constant micromotion were analysed from the perspective of elastic wave propagation. When the slip plane of the dangerous rock mass is damaged, many micropores and cracks will appear in the medium composed of the slip surface. With constant micromotion as the vibration source, the elastic wave propagates to the dangerous rock mass through the damaged slip plane. The high-frequency components of elastic waves scatter in pores and fissures, where energy dissipates. According to this characteristic, a laboratory simulation experiment was designed. In the experiment, the damage process of the slip plane was simulated by the freeze‒thaw process of frozen hydrosol. The experimental analysis showed that the centre frequency of the high-frequency part of the dangerous rock mass model and bedrock mass model decreased as the frozen surface continued to melt. As the dangerous rock mass model and the bedrock mass model continued to fit, the centre frequency of the high-frequency part of the two rock mass models rebounded. This phenomenon showed that the damage degree of the slip plane between the dangerous rock mass and the bed rock mass can be effectively reflected by the centre frequency of the high-frequency part of the two rock mass models. During the experiment, the dangerous rock mass did not slide in the whole process, indicating that the deformation index has difficulty reflecting the stability of the hidden dangerous rock mass. In addition, the application conditions of using the natural frequency characteristics of dangerous rock mass and the scattering characteristics of elastic wave in the damage identification of structural plane were analysed: (1) when the structural plane has macrofracture, the change of natural frequency of dangerous rock mass should be used to analyse the damage degree of structural plane; (2) when there is no macrofracture of the structural plane, the characteristics of elastic wave scattering should be used to analyse the damage degree of the structural plane. This study provided a new idea for the prevention and control of dangerous rock masses and is expected to provide a useful reference for the automation of dangerous rock mass prevention and control.

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Section: Experimental Data Processing Methodmentioning

confidence: 99%

Experimental Study on the Vibration Characteristics of Dangerous Rock Mass under Constant Micromotion

Zhang

Xie

Huang

et al. 2023

Advances in Civil Engineering

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“…However, there are some problems with the EMD method, of which the main one is mode mixing. Complementary ensemble empirical mode decomposition (CEEMD) can effectively restrain the mode mixing of EMD at a certain level [ 23 , 24 , 25 ]. Based on the above considerations, we proposed a new algorithm which combines CEEMD with permutation entropy (PE) [ 26 ] to effectively improve the complexity of the digital chaotic sequence.…”

Section: Introductionmentioning

confidence: 99%

A Novel Algorithm to Improve Digital Chaotic Sequence Complexity through CCEMD and PE

Fan

Xie

Ding

2018

Entropy

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In this paper, a three-dimensional chaotic system with a hidden attractor is introduced. The complex dynamic behaviors of the system are analyzed with a Poincaré cross section, and the equilibria and initial value sensitivity are analyzed by the method of numerical simulation. Further, we designed a new algorithm based on complementary ensemble empirical mode decomposition (CEEMD) and permutation entropy (PE) that can effectively enhance digital chaotic sequence complexity. In addition, an image encryption experiment was performed with post-processing of the chaotic binary sequences by the new algorithm. The experimental results show good performance of the chaotic binary sequence.Empirical mode decomposition (EMD) in digital signal processing has been extensively applied in nonlinear signal processing [15][16][17][18]. EMD was first proposed by Huang et al. [19][20][21]. It is an effective tool for analyzing nonlinear and non-stationary signals. The EMD method is closely related to the corresponding Hilbert transform method. Through the decomposition of nonlinear and non-stationary signals, a series of intrinsic mode functions (IMFs) are obtained, which makes each IMF a stable signal for narrowband [22]. The IMFs play a crucial role in the analysis of non-stationary or nonlinear signals. However, there are some problems with the EMD method, of which the main one is mode mixing. Complementary ensemble empirical mode decomposition (CEEMD) can effectively restrain the mode mixing of EMD at a certain level [23][24][25]. Based on the above considerations, we proposed a new algorithm which combines CEEMD with permutation entropy (PE) [26] to effectively improve the complexity of the digital chaotic sequence.The rest of this paper is organized as follows: Section 2 describes a hidden chaos attractor with no equilibria. The dynamic characteristics of a complex chaotic system are studied by means of numerical simulation and theoretical analysis. Section 3 proposes a new algorithm to improve the complexity of the digital chaotic sequence. Section 4 considers image encryption with post-processing of the chaotic binary sequences by the algorithm outlined in Section 3. The security of the encrypted image is analyzed through key sensitivity, information entropy, and histogram analysis. Section 5 summarizes the discussions of this paper. The Characteristic Analysis of a Chaotic SystemIn this section, a system can be expressed as the following set of differential equations:where a, b, c are real parameters. When a = 2, b = 0.35, c = 1 and the initial value is (−1.6, 0.82, 1.9), the system displays a single-scroll chaotic system [27]. Different projections of the chaotic attractor for this system are shown in Figure 1.

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Dynamic monitoring and data analysis of a long-span arch bridge based on high-rate GNSS-RTK measurement combining CF-CEEMD method

Niu

Zhao

et al. 2020

J Civil Struct Health Monit

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Artificial accelerograms composition based on the CEEMD

Cited by 4 publications

References 19 publications

Experimental Study on the Vibration Characteristics of Dangerous Rock Mass under Constant Micromotion

Experimental Study on the Vibration Characteristics of Dangerous Rock Mass under Constant Micromotion

A Novel Algorithm to Improve Digital Chaotic Sequence Complexity through CCEMD and PE

Dynamic monitoring and data analysis of a long-span arch bridge based on high-rate GNSS-RTK measurement combining CF-CEEMD method

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