Dynamical Behaviors Analysis of the Rotor Model with Coupling Faults and Applications of the TPOD Method

Lu, Kuan; Wu, Nan; Zhang, Kangyu; Fu, Chao; Jin, Yulin; Yang, Yue; Zhang, Haopeng

doi:10.3390/app10217415

Cited by 3 publications

(1 citation statement)

References 61 publications

(64 reference statements)

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“…The purpose of greatly reducing the number of degrees of freedom is achieved by reducing the basis vector. Lu Kuan et al [59] improved the traditional POD method based on the inertial manifold theory, perfected the transient POD method, and proposed the method of determining the optimal dimensionality reduction model of the original high-dimensional complex system based on the physical meaning of the transient POD method. The improved POD method is used to reduce the dimensions of the original rotor-bearing system.…”

Section: Mode Decomposition In Nonlinear Vibration Systemsmentioning

confidence: 99%

Research, Application and Future Prospect of Mode Decomposition in Fluid Mechanics

Long,

Guo,

Xiao

2024

Symmetry

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In fluid mechanics, modal decomposition, deeply intertwined with the concept of symmetry, is an essential data analysis method. It facilitates the segmentation of parameters such as flow, velocity, and pressure fields into distinct modes, each exhibiting symmetrical or asymmetrical characteristics in terms of amplitudes, frequencies, and phases. This technique, emphasizing the role of symmetry, is pivotal in both theoretical research and practical engineering applications. This paper delves into two dominant modal decomposition methods, infused with symmetry considerations: Proper Orthogonal Decomposition (POD) and Dynamic Mode Decomposition (DMD). POD excels in dissecting flow fields with clear periodic structures, often showcasing symmetrical patterns. It utilizes basis functions and time coefficients to delineate spatial modes and their evolution, highlighting symmetrical or asymmetrical transitions. In contrast, DMD effectively analyzes more complex, often asymmetrical structures like turbulent flows. By performing iterative analyses on the flow field, DMD discerns symmetrical or asymmetrical statistical structures, assembling modal functions and coefficients for decomposition. This method is adapted to extracting symmetrical patterns in vibration frequencies, growth rates, and intermodal coupling. The integration of modal decomposition with symmetry concepts in fluid mechanics enables the effective extraction of fluid flow features, such as symmetrically or asymmetrically arranged vortex configurations and trace evolutions. It enhances the post-processing analysis of numerical simulations and machine learning approaches in flow field simulations. In engineering, understanding the symmetrical aspects of complex flow dynamics is crucial. The dynamics assist in flow control, noise suppression, and optimization measures, thus improving the symmetry in system efficiency and energy consumption. Overall, modal decomposition methods, especially POD and DMD, provide significant insights into the symmetrical and asymmetrical analysis of fluid flow. These techniques underpin the study of fluid mechanics, offering crucial tools for fluid flow control, optimization, and the investigation of nonlinear phenomena and propagation modes in fluid dynamics, all through the lens of symmetry.

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Section: Mode Decomposition In Nonlinear Vibration Systemsmentioning

confidence: 99%

Research, Application and Future Prospect of Mode Decomposition in Fluid Mechanics

Long,

Guo,

Xiao

2024

Symmetry

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Research of energy characteristics and fault position detection for cracked rotor system

Zhang

Yong

Gao

et al. 2023

Journal of Sound and Vibration

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Application of Vibration Signal Processing Methods to Detect and Diagnose Wheel Flats in Railway Vehicles

et al. 2021

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This paper studied two useful vibration signal processing methods for detection and diagnosis of wheel flats. First, the cepstrum analysis method combined with order analysis was applied to the vibration signal to detect periodic responses in the spectrum for a rotating body such as a wheel. In the case of railway vehicles, changes in speed occur while driving. Thus, it is difficult to effectively evaluate the flat signal of the wheel because the time cycle of the flat signal changes frequently. Thus, the order analysis was combined with the existing cepstrum analysis method to consider the changes in train speed. The order analysis changes the domain of the vibration signal from time domain to rotating angular domain to consider the train speed change in the cepstrum analysis. Second, the cross correlation analysis method combined with the order analysis was applied to evaluate the flat signal from the vibration signal well containing the severe field noise produced by the vibrations of the rail irregularities and bogie components. Unlike the cepstrum analysis method, it can find out the wheel flat size because the flat signal linearly increases to the wheel flat. Thus, it is more effective when checking the size of the wheel flat. Finally, the data tested in the Korea Railroad Research Institute were used to confirm that the cepstrum analysis and cross correlation analysis methods are appropriate for not only simulation but also test data.

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Dynamical Behaviors Analysis of the Rotor Model with Coupling Faults and Applications of the TPOD Method

Cited by 3 publications

References 61 publications

Research, Application and Future Prospect of Mode Decomposition in Fluid Mechanics

Research, Application and Future Prospect of Mode Decomposition in Fluid Mechanics

Research of energy characteristics and fault position detection for cracked rotor system

Application of Vibration Signal Processing Methods to Detect and Diagnose Wheel Flats in Railway Vehicles

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