scholarly journals An Instantaneous Frequency Identification Algorithm for Time-Varying Frequency Signals

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 165345-165355
Author(s):  
Li Xiaocong ◽  
Meng Xuanren
Author(s):  
Mohammad A. AL-Shudeifat

The frequency of the purely nonlinear and non-conservative oscillator is a time-varying quantity due to the presence of damping. For the nonlinear oscillator addressed here, only cubic-power stiffness nonlinearity is considered. The nonlinear frequency of the conservative nonlinear oscillator is dependent on the initial energy induced into the system. However, for the non-conservative and purely nonlinear oscillator, the instantaneous frequency is dependent on the instantaneous energy of the system. Consequently, the exact amplitude decay formula obtained in a recent publication for such oscillator is accurately applied here to obtain an accurate analytical formula for the time-varying frequency of the considered system. Excellent agreement between the results obtained by the new time-varying frequency formula presented here and both numerical simulation and wavelet transform has been clearly observed. This analytical formula is found to be accurate in identifying the instantaneous frequency change of the system regardless of its physical parameters and the initial input energies.


2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Chang Xu ◽  
Cong Wang ◽  
Jingbo Gao

An instantaneous frequency identification method of vibration signal based on linear chirplet transform and Wigner-Ville distribution is presented. This method has an obvious advantage in identifying closely spaced and time-varying frequencies. The matching pursuit algorithm is employed to select optimal chirplets, and a modified version of chirplet transform is presented to estimate nonlinear varying frequencies. Because of the high time resolution, the modified chirplet transform is superior to the original method. The proposed method is applied to time-varying systems with both linear and nonlinear varying stiffness and systems with closely spaced modes. A wavelet-based identification method is simulated to compare with the proposed method, with the comparison results showing that the chirplet-based method is effective and accurate in identifying both time-varying and closely spaced frequencies. A bat echolocation signal is used to verify the effectiveness of the modified chirplet transform. The result shows that it will significantly increase the accuracy of nonlinear frequency trajectory identification.


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