When disturbed, the interaction between power grid and wind farm may cause serious sub/super-synchronous oscillation (SSO), affecting the security and stability of the system. It is therefore important to detect the t...When disturbed, the interaction between power grid and wind farm may cause serious sub/super-synchronous oscillation (SSO), affecting the security and stability of the system. It is therefore important to detect the time-varying amplitude and frequency of SSO to provide information for its control. The matching synchroextracting wavelet transform (MSEWT) is a new method proposed in this paper to serve this purpose. Based on the original synchrosqueezing wavelet transform, MSEWT uses a synchronous extraction operator to calculate the time-frequency coefficients and a chirp-rate estimation to modify the instantaneous frequency estimation. Thus, MSEWT can improve the concentration degree and reconstruction accuracy of the signal's time-frequency representation without iterative calculation, and can achieve superior noise robustness. After the time-frequency analysis and modal decomposition of the SSO by MSEWT, the amplitudes and frequencies of each oscillation component can be obtained by Hilbert transform (HT). The simulation studies demonstrate that the proposed scheme can accurately identify the modal parameters of SSO even in the case of noise interference, providing a reliable reference for stable operation of power system time-frequency.展开更多
Several popular time-frequency techniques,including the Wigner-Ville distribution,smoothed pseudo-Wigner-Ville distribution,wavelet transform,synchrosqueezing transform,Hilbert-Huang transform,and Gabor-Wigner transfo...Several popular time-frequency techniques,including the Wigner-Ville distribution,smoothed pseudo-Wigner-Ville distribution,wavelet transform,synchrosqueezing transform,Hilbert-Huang transform,and Gabor-Wigner transform,are investigated to determine how well they can identify damage to structures.In this work,a synchroextracting transform(SET)based on the short-time Fourier transform is proposed for estimating post-earthquake structural damage.The performance of SET for artificially generated signals and actual earthquake signals is examined with existing methods.Amongst other tested techniques,SET improves frequency resolution to a great extent by lowering the influence of smearing along the time-frequency plane.Hence,interpretation and readability with the proposed method are improved,and small changes in the time-varying frequency characteristics of the damaged buildings are easily detected through the SET method.展开更多
In recent years,much research has been focused on separating acoustic sources from their mixtures.Degenerate Unmixing Estimation Technique(DUET)is one of the widely popular meth-ods of Blind Source Separation(BSS)in u...In recent years,much research has been focused on separating acoustic sources from their mixtures.Degenerate Unmixing Estimation Technique(DUET)is one of the widely popular meth-ods of Blind Source Separation(BSS)in underdetermined scenarios.DUET is based on a signal recovery sparsity algorithm whose performance is strongly influenced by sparsity in the Time-Frequency(TF)domain.Noises and an several sources in mixtures limit the sparsity resulting in performance degradation in DUET.Here an enhanced strategy has been adopted by combin-ing DUET with adaptive noise cancellation utilising the Dual-Tree Complex Wavelet Transform(DTCWT)as a pre-processor and TF refinement utilising Synchroextracting Transform(SET)as a post-processor.This improves the sparsity of sources and energy concentrations in a TF rep-resentation.Results of the signal separation performance evaluation reveal that the proposed algorithm outperforms conventional DUET in signal separation,especially in real-time scenarios.展开更多
基金supported by National Natural Science Foundation of China(No.52077081)Guangdong Basic and Applied Basic Research Foundation(No.2022A1515011608).
文摘When disturbed, the interaction between power grid and wind farm may cause serious sub/super-synchronous oscillation (SSO), affecting the security and stability of the system. It is therefore important to detect the time-varying amplitude and frequency of SSO to provide information for its control. The matching synchroextracting wavelet transform (MSEWT) is a new method proposed in this paper to serve this purpose. Based on the original synchrosqueezing wavelet transform, MSEWT uses a synchronous extraction operator to calculate the time-frequency coefficients and a chirp-rate estimation to modify the instantaneous frequency estimation. Thus, MSEWT can improve the concentration degree and reconstruction accuracy of the signal's time-frequency representation without iterative calculation, and can achieve superior noise robustness. After the time-frequency analysis and modal decomposition of the SSO by MSEWT, the amplitudes and frequencies of each oscillation component can be obtained by Hilbert transform (HT). The simulation studies demonstrate that the proposed scheme can accurately identify the modal parameters of SSO even in the case of noise interference, providing a reliable reference for stable operation of power system time-frequency.
文摘Several popular time-frequency techniques,including the Wigner-Ville distribution,smoothed pseudo-Wigner-Ville distribution,wavelet transform,synchrosqueezing transform,Hilbert-Huang transform,and Gabor-Wigner transform,are investigated to determine how well they can identify damage to structures.In this work,a synchroextracting transform(SET)based on the short-time Fourier transform is proposed for estimating post-earthquake structural damage.The performance of SET for artificially generated signals and actual earthquake signals is examined with existing methods.Amongst other tested techniques,SET improves frequency resolution to a great extent by lowering the influence of smearing along the time-frequency plane.Hence,interpretation and readability with the proposed method are improved,and small changes in the time-varying frequency characteristics of the damaged buildings are easily detected through the SET method.
文摘In recent years,much research has been focused on separating acoustic sources from their mixtures.Degenerate Unmixing Estimation Technique(DUET)is one of the widely popular meth-ods of Blind Source Separation(BSS)in underdetermined scenarios.DUET is based on a signal recovery sparsity algorithm whose performance is strongly influenced by sparsity in the Time-Frequency(TF)domain.Noises and an several sources in mixtures limit the sparsity resulting in performance degradation in DUET.Here an enhanced strategy has been adopted by combin-ing DUET with adaptive noise cancellation utilising the Dual-Tree Complex Wavelet Transform(DTCWT)as a pre-processor and TF refinement utilising Synchroextracting Transform(SET)as a post-processor.This improves the sparsity of sources and energy concentrations in a TF rep-resentation.Results of the signal separation performance evaluation reveal that the proposed algorithm outperforms conventional DUET in signal separation,especially in real-time scenarios.
