Identification of complex non-linear modes of mechanical systems using the Hilbert-Huang transform from free decay responses

Ondra, Václav; Sever, Ibrahim A.; Schwingshackl, Christoph W.

doi:10.1016/j.jsv.2020.115912

Cited by 11 publications

(2 citation statements)

References 63 publications

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“…The HHT is equivalent to an interesting filter, in which the amplitude of the spectral components remains unchanged, but their phases are shifted by one [32,33]. Its unit impulse response is 1/πt.…”

Section: Hilbert-huang Transformmentioning

confidence: 99%

Fusion Method and Application of Several Source Vibration Fault Signal Spatio-Temporal Multi-Correlation

Cheng

et al. 2021

Applied Sciences

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Combined with other signal processing methods, related algorithms are widely used in the diagnosis and identification of rotor faults. In order to solve the problem that the vibration signal of a single sensor is too single, a new multi-source vibration signal fusion method is proposed. This method explores the correlation between vibration sensors at different locations by using multiple cross-correlations of spatial locations. First, wavelet noise reduction and linear normalization are used to process the original data. Then, the signal energy correlation function between the sensors is established, and the adaptive weight is obtained. Finally, the data fusion result is obtained. Taking rotor bearing and gear failures at different speeds as an example, the data of three vibration sensors at different positions are fused using the spatio-temporal multiple correlation fusion method (STMF). Through the intelligent fault diagnosis method stacked auto encoder (SAE), compared with single sensor data, average weighted fusion data and neural network fusion data, STMF method can reach a diagnosis accuracy of more than 94% at 700 rpm, 900 rpm and 1100 rpm. It is concluded that the result of the STMF method is more effective and superior.

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Section: Hilbert-huang Transformmentioning

confidence: 99%

Fusion Method and Application of Several Source Vibration Fault Signal Spatio-Temporal Multi-Correlation

Cheng

et al. 2021

Applied Sciences

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“…Lum is with the Department of Electrical Engineering, National Chi Nan University, 54561 Taiwan (e-mail: kylum@ncnu.edu.tw). [18], and identification and fault diagnosis of nonlinear mechanical systems [19]- [21]. Meanwhile, improved formulations have been proposed, notably ensemble EMD (EEMD) for noise-assisted decomposition and clutter rejection [22], [23] and the use of masking signals to prevent mode mixing [24].…”

Section: A General Backgroundmentioning

confidence: 99%

Bootstrap Empirical Mode Decomposition with Application to CIELAB Color Images

Lum¹

2021

Preprint

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This paper proposes an alternative optimization-based EMD based on the notions of: 1. <i>local mean points </i>that impose mode symmetry via a Tikhonov regularized least-square (RLS) problem, and 2. efficient <i>bootstrap sifting</i> that guarantees asymptotic convergence of the mean envelope to the local mean points, regardless of regularization. Mathematical proof of convergence and a straightforward extension to the 2D-multivariate setting and CIELAB color image sare presented. Performance is demonstrated with a univariate signal and two images. Spectral analysis confirms coordinated feature extraction among image components, and separation of spatial spectra among the intrinsic mode functions.

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A strain transmissibility-based analysis approach for operational modal of concrete dam under nonstationary excitation

Fang,

Su,

Zuo

et al. 2024

Engineering Fracture Mechanics

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Identification of complex non-linear modes of mechanical systems using the Hilbert-Huang transform from free decay responses

Cited by 11 publications

References 63 publications

Fusion Method and Application of Several Source Vibration Fault Signal Spatio-Temporal Multi-Correlation

Fusion Method and Application of Several Source Vibration Fault Signal Spatio-Temporal Multi-Correlation

Bootstrap Empirical Mode Decomposition with Application to CIELAB Color Images

A strain transmissibility-based analysis approach for operational modal of concrete dam under nonstationary excitation

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