The Research Of Some Problems In Nonstationary Signals Time-Frequency Joint Analysis Methods And Application

Strictly speaking, the natural signals are all nonstationary signals. How to measure these kinds of signals and estimate their characteristics effectively is widely discussed by the researchers in measurement domain.The classic signal procession methods describe the signals in the time or frequency domain separately. Since the characteristics of nonstationary signals are varying by time, the traditional approaches are less effective.Time-Frequency Joint Analysis (TFJA) theory works more effectively in nonstationary signal analysis. It analyzes the signals in the time-frequency joint domain. The time-varying characteristics of nonstationary signals can be effectively extracted through the TFJA.In this thesis, various nonstationary signals analyzing approaches in the measurement system are discussed:(1) The aliasing restraining of the limited bandwidth nonsationary signals analysis based on the Short Time Fourier TransformFirstly, the performance of nonstationary signal analyzed by STFT is discussed, and the result shows that STFT can extract the characteristics of limited bandwidth signals effectively.And then, an optimized algorithm is proposed to restrain the aliasing. The physical essence of occurred aliasing is discussed. The filter window selected technical is described. Based on the interpolation method in the frequency domain, the STFT is optimized. Using the Newton iterative method, the fast computation of algorithm is implemented.(2) The research of the frequency band leakage and oscillation of the transient signals processing based on the Wavelet Packet Transform (WPT)In this section, aiming at the leakage occurred during the WPT, an optimized algorithm is proposed. Firstly, the performance of the WPT analysis of the nonsationary transient signals is discussed, and the advantage is pointed out. The leakage caused by the incompactly support of the function is investigated.And then a novel optimized algorithm in time domain is brought forward. By the algorithm, the compact support character in frequency domain of wavelet packet function is reserved, and the performance in time domain is improved. The simulation proved the effectiveness of the algorithm.(3) The research of "limited data length effect" in the WPTBecause the essence of the WPT is a kind of "windowed" transform, during the course of analyzing the signal, the sampled data should be truncated inevitably. The truncation causes the "limited data length effect", and brings on the band leakage.Aiming at this problem, based on the Gibbs theory, a kind of WPT frequency filter interpolation algorithm is bring forward to suppress those unwanted effect. The fast computation of interpolation is implemented, and the quantity of interpolating points is discussed.(4) The research on the output Signal-to-Noise Ration (SNR) of the Wigner-Hough Transform (WHT) in the Linear Frequency Modulation (LFM) signal detectionThe advantage and disadvantage of using WHT to detect the multi-component LFM signals are discussed.Output SNR is deteriorated because the varying of the signal input SNR and the available data number. Aiming at these deteriorative factors, the thesis researches the relation of the factors in depth. The mathematic relation of them is deducted. A novel algorithm is brought forward based on the PWHT and interpolation. The simulation result proves the effectiveness of the algorithm.(5) The application of the algorithms in engineering projectsThe algorithms in this thesis are validated in engineering projects.Firstly, the nonsatationary characteristics of voltage and current that are caused by industry electromotor control system in the power system are researched.An engineering test model is set up to validate the algorithm in the 3^rd chapter.The industry electromotor control system is used in this model. Because the trigger angle and the load of the motor are varying by time, the voltage and current in power system are changing too. Applied the optimized WPT in chapter 3, the characters of the varying voltage and current can be extracted effectively.Secondly, a project is set up to validate the algorithm in the 4^th chapter.Applied the optimized WHT algorithm, the parameters of multi-components LFM signals in strong noise background can be correctly extracted, and the time varying characters of signals are shown clearly.