A novel instantaneous frequency estimation method for operational time-varying systems using short-time multivariate variational mode decomposition

Liu, Shuaishuai; Zhao, Rui; Yu, Kaiping; Liao, Baopeng; Zheng, Bowen

doi:10.1177/10775463221109699

Cited by 3 publications

(2 citation statements)

References 37 publications

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“…Different from recursive decomposition algorithms such as EMD, VMD searches variational modes through iterative methods and decomposes signals into IMF components of different frequency bands. VMD has good applications in fault diagnosis [ 34 , 35 ], signal noise reduction [ 36 ] and parameter identification [ 37 ]. The specific calculation method of VMD is as follows:…”

Section: Methods and Principlesmentioning

confidence: 99%

A Multistep Prediction Model for the Vibration Trends of Hydroelectric Generator Units Based on Variational Mode Decomposition and Stochastic Configuration Networks

Yan,

Chen,

Yang

et al. 2023

Sensors

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Accurately predicting the changes in turbine vibration trends is a key part of the operational condition maintenance of hydropower units, which is of great significance for improving both the operational condition and operational efficiency of hydropower plants. In this paper, we propose a multistep prediction model for the vibration trend of a hydropower unit. This model is based on the theoretical principles of signal processing and machine learning, incorporating variational mode decomposition (VMD), stochastic configuration networks (SCNs), and the recursive strategy. Firstly, in view of the severe fluctuations of the vibration signal of the unit, this paper decomposes the unit vibration data into intrinsic mode function (IMF) components of different frequencies by VMD, which effectively alleviates the instability of the vibration trend. Secondly, an SCN model is used to predict different IMF components. Then, the predicted values of all the IMF components are superimposed to form the prediction results. Finally, according to the recursive strategy, a multistep prediction model of the HGU’s vibration trends is constructed by adding new input variables to the prediction results. This model is applied to the prediction of vibration data from different components of a unit, and the experimental results show that the proposed multistep prediction model can accurately predict the vibration trend of the unit. The proposed multistep prediction model of the vibration trends of hydropower units is of great significance in guiding power plants to adjust their control strategies to reach optimal operating efficiency.

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Section: Methods and Principlesmentioning

confidence: 99%

A Multistep Prediction Model for the Vibration Trends of Hydroelectric Generator Units Based on Variational Mode Decomposition and Stochastic Configuration Networks

Yan,

Chen,

Yang

et al. 2023

Sensors

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show abstract

“…It requires a proper model of the input signal and generally their computational requirements for real-time implementation on industrial systems are enormous and difficult (Pasand and Taherkhani, 2021). Also, recently some hybrid methods have proposed to extract instantaneous frequency of the signals (Daneshvar and Salehi, 2022; Liu et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Online frequency estimation of periodic disturbance based on FFT algorithm with application in repetitive control

Moghadam

Vasegh

Mousavi

2023

Journal of Vibration and Control

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In this paper, a new adaptive method is proposed for online frequency estimation of a periodic disturbance by the output measurement based on the fast Fourier transform algorithm. The performance of the proposed algorithm is evaluated in the face of time varying frequency, time varying amplitude, non-sinusoidal periodic disturbance, and different plants. Also, the convergence rate of the method is compared by other estimation methods. Then, the online estimation is used in the repetitive controller structure for eliminating periodic disturbances with unknown frequencies. A new analysis is performed on RC and the stability conditions are determined in a theorem. These are illustrated in simulation results. The effectiveness of this method is shown on the application of ϕ-shaped PZT active suspension and it is compared by existing results.

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Output-Only Time-Varying Modal Parameters Identification Using Recursive Subspace Algorithm Based Modified FAPI

Jiang,

Wang

2024

Lecture Notes in Mechanical Engineering

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A novel instantaneous frequency estimation method for operational time-varying systems using short-time multivariate variational mode decomposition

Cited by 3 publications

References 37 publications

A Multistep Prediction Model for the Vibration Trends of Hydroelectric Generator Units Based on Variational Mode Decomposition and Stochastic Configuration Networks

A Multistep Prediction Model for the Vibration Trends of Hydroelectric Generator Units Based on Variational Mode Decomposition and Stochastic Configuration Networks

Online frequency estimation of periodic disturbance based on FFT algorithm with application in repetitive control

Output-Only Time-Varying Modal Parameters Identification Using Recursive Subspace Algorithm Based Modified FAPI

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