Existing sequential parameter estimation methods use the acoustic pressure of a line array as observations. The modal dispersion curves are employed to estimate the sound speed profile（SSP） and geoacoustic parameter...Existing sequential parameter estimation methods use the acoustic pressure of a line array as observations. The modal dispersion curves are employed to estimate the sound speed profile（SSP） and geoacoustic parameters based on the ensemble Kalman filter. The warping transform is implemented to the signals received by a single hydrophone to obtain the dispersion curves. The experimental data are collected at a range-independent shallow water site in the South China Sea. The results indicate that the SSPs are well estimated and the geoacoustic parameters are also well determined. Comparisons of the observed and estimated modal dispersion curves show good agreement.展开更多
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
基金Supported by the National Natural Science Foundation of China under Grant Nos 11434012,11774374,11404366 and41561144006
文摘Existing sequential parameter estimation methods use the acoustic pressure of a line array as observations. The modal dispersion curves are employed to estimate the sound speed profile（SSP） and geoacoustic parameters based on the ensemble Kalman filter. The warping transform is implemented to the signals received by a single hydrophone to obtain the dispersion curves. The experimental data are collected at a range-independent shallow water site in the South China Sea. The results indicate that the SSPs are well estimated and the geoacoustic parameters are also well determined. Comparisons of the observed and estimated modal dispersion curves show good agreement.
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.
