Time–frequency representation of earthquake accelerograms and inelastic structural response records using the adaptive chirplet decomposition and empirical mode decomposition

Spanos, Pol D.; Giaralis, Agathoklis; Politis, Nikolaos

doi:10.1016/j.soildyn.2006.11.007

Cited by 108 publications

(44 citation statements)

References 24 publications

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“…Arguably, such a consideration is better addressed by means of time-frequency representation techniques (see e.g. Spanos et al 2007a, Spanos et al 2007b and references therein), or by means of adaptive (i.e., time-varying) filter models (see e.g. Ahmadi 1990, Rezaeian andDer Kiureghian 2010) applied to field recorded accelerograms.…”

Section: Discussionmentioning

confidence: 99%

Derivation of response spectrum compatible non-stationary stochastic processes relying on Monte Carlo-based peak factor estimation

Giaralis¹,

Spanos²

2012

Earthquakes and Structures

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Abstract. In this paper a novel non-iterative approach is proposed to address the problem of deriving non-stationary stochastic processes which are compatible in the mean sense with a given (target) response (uniform hazard) spectrum (UHS) as commonly desired in the aseismic structural design regulated by contemporary codes of practice. This is accomplished by solving a standard over-determined minimization problem in conjunction with appropriate median peak factors. These factors are determined by a plethora of reported new Monte Carlo studies which on their own possess considerable stochastic dynamics merit. In the proposed approach, generation and treatment of samples of the processes individually on a deterministic basis is not required as is the case with the various approaches found in the literature addressing the herein considered task. The applicability and usefulness of the approach is demonstrated by furnishing extensive numerical data associated with the elastic design UHS of the current European (EC8) and the Chinese (GB 50011) aseismic code provisions. Purposely, simple and thus attractive from a practical viewpoint, uniformly modulated processes assuming either the Kanai-Tajimi (K-T) or the Clough-Penzien (C-P) spectral form are employed. The Monte Carlo studies yield damping and duration dependent median peak factor spectra, given in a polynomial form, associated with the first passage problem for UHS compatible K-T and C-P uniformly modulated stochastic processes. Hopefully, the herein derived stochastic processes and median peak factor spectra can be used to facilitate the aseismic design of structures regulated by contemporary code provisions in a Monte Carlo simulationbased or stochastic dynamics-based context of analysis.

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Section: Discussionmentioning

confidence: 99%

Derivation of response spectrum compatible non-stationary stochastic processes relying on Monte Carlo-based peak factor estimation

Giaralis¹,

Spanos²

2012

Earthquakes and Structures

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“…In order to scrutinize the variation of the frequency content with respect to time the mean instantaneous frequency is introduced [29, 33,34],…”

Section: Influence Of the Corrective Termmentioning

confidence: 99%

A stochastic approach for generating spectrum compatible fully nonstationary earthquakes

Cacciola

2010

Computers & Structures

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Simulation of artificial earthquakes in agreement with the provision of international seismic codes is addressed. Due to the importance of nonstationary frequency content on the seismic assessment of structures, in this paper a new method for generating spectrum compatible fully nonstationary earthquakes is proposed. The method assumes that the ground motion is modeled by the superposition of two contributions: the first one is a fully nonstationary counterpart modeled by a recorded earthquake; the second one is a corrective random process adjusting the recorded earthquake in order to make it spectrum compatible. Several examples show the accuracy of the proposed method.

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“…Thus, STFT is suitable for processing quasi stationary signals instead of realistic non-linear and non-stationary signals [13]. Wigner-Ville distribution has a high time and frequency resolution, but its application is restricted in multicomponent signal analysis because of cross-product term interferences [19,20]. Compared with STFT, wavelet transform is a more effective tool in analyzing non-linear and non-stationary signals because of its property on multi-resolution analysis.…”

Section: Introductionmentioning

confidence: 99%

Fault diagnosis of motorized spindle via modified empirical wavelet transform-kernel PCA and optimized support vector machine

Chen¹,

Ye²,

Chen³

et al. 2017

J. vibroeng.

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Abstract. The fault diagnosis of motorized spindle contributes to the improvement of the reliability of computer numerical control machine tools. Presently, numerous mechanical fault diagnosis technologies suffer from the drawbacks of mode mixing, non-adaptive analysis, and low efficiency. Therefore, adopting an effective signal processing method for fault diagnosis of motorized spindle is essential. A method based on modified empirical wavelet transform (EWT) and kernel principal component analysis (Kernel PCA) is proposed. A new method, which determines the proper number of the Fourier spectrum segments, is applied when using EWT. To improve computational efficiency, Kernel PCA is adopted to reduce dimension. The support vector machine optimized by genetic algorithm is introduced to accomplish fault identification. The performance of the proposed method is validated through single and compound fault experiments. Results show that the recognition rate using the proposed method reached 98.8095 % and 98.4375 % in terms of single and compound fault diagnoses, respectively. Moreover, compared with empirical mode decomposition (EMD), ensemble empirical mode decomposition (EEMD), local mean decomposition (LMD) and EWT, the proposed method can save much computing time. The proposed method can be generalized to other mechanical fault diagnoses as well.

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Time–frequency representation of earthquake accelerograms and inelastic structural response records using the adaptive chirplet decomposition and empirical mode decomposition

Cited by 108 publications

References 24 publications

Derivation of response spectrum compatible non-stationary stochastic processes relying on Monte Carlo-based peak factor estimation

Derivation of response spectrum compatible non-stationary stochastic processes relying on Monte Carlo-based peak factor estimation

A stochastic approach for generating spectrum compatible fully nonstationary earthquakes

Fault diagnosis of motorized spindle via modified empirical wavelet transform-kernel PCA and optimized support vector machine

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