Title :
Spline-Kernelled Chirplet Transform for the Analysis of Signals With Time-Varying Frequency and Its Application
Author :
Yang, Y. ; Peng, Z.K. ; Meng, G. ; Zhang, W.M.
Author_Institution :
State Key Lab. of Mech. Syst. & Vibration, Shanghai Jiao Tong Univ., Shanghai, China
fDate :
3/1/2012 12:00:00 AM
Abstract :
The conventional time-frequency analysis (TFA) methods, including continuous wavelet transform, short-time Fourier transform, and Wigner-Ville distribution, have played important roles in analyzing nonstationary signals. However, they often show less capability in dealing with nonstationary signals with time-varying frequency due to the bad energy concentration in the time-frequency plane. On the other hand, by introducing an extra transform kernel that matches the instantaneous frequency of the signal, parameterized TFA methods show powerful ability in characterizing time-frequency patterns of nonstationary signals with time-varying frequency. In this paper, a novel time-frequency transform, called spline-kernelled chirplet transform (SCT), is proposed. By introducing a frequency-rotate operator and a frequency-shift operator constructed with spline kernel function, the SCT is particularly powerful for the strongly nonlinear frequency-modulated signals. In addition, an effective algorithm is developed to estimate the parameters of transform kernel in the SCT. The capabilities of the SCT and parameter estimation algorithm are validated by their applications for numerical signals and a set of vibration signal collected from a rotor test rig.
Keywords :
Fourier transforms; electric machines; frequency modulation; parameter estimation; rotors; signal processing; time-frequency analysis; SCT; TFA methods; Wigner-Ville distribution; continuous wavelet transform; energy concentration; frequency-rotate operator; frequency-shift operator; nonlinear frequency-modulated signals; rotor test rig; short-time Fourier transform; signal analysis; spline-kernelled chirplet transform; time-frequency transform analysis; time-varying frequency; vibration signal; Approximation methods; Chirp; Kernel; Polynomials; Splines (mathematics); Time frequency analysis; Transforms; Chirplet transform (CT); instantaneous frequency (IF); spline-kernelled chirplet transform (SCT); time–frequency representation (TFR);
Journal_Title :
Industrial Electronics, IEEE Transactions on
DOI :
10.1109/TIE.2011.2163376