The Comparison Of Time-Frequency Analysis On The Feature Extraction Of Maglev´ Track Long-Wave Irregularity

In the signal processing, the theories and methods, such as optimization, auto-adaptive, high resolution and multi-dimension, is become systematic. We are looking forward to higher research. Many people are focusing on the signal of non-stationary, non-Guassian, non-minimum phase, nonlinear system and so on. As a result, the method of the analysis is changed from time analysis and frequency analysis to time-frequency analysis. In this paper, we simulate the data of the maglev´ track, according to the data from the real testing of the maglev on the railway. Some typical time-frequency method is used to analyze the data, to estimate and recompose the track irregularity signal, including short time Fourier transform (STFT), Wigner-Ville distribution(WVD), Gabor distribution(DGS), Hilbert-Huang transform(HHT), and wavelet transform(WT). On the base of the analytic results, the difference of each method, which is used to analyze the data of maglev´ track in this paper, is compared. Some feature of the method is given in this application. Because of the purpose of this thesis to complete the engineering project, all of the arithmetic programs in this system have been validated in practice. According to the analysis of practical measurement, the measurement system is proved to be a success and the performance meets the expectations.