基于平稳小波包分解的水轮机非平稳振动信号希尔伯特谱分析

应用平稳小波包变换对信号进行窄带分解,避免了经验模式分解过程中虚假模式分量的产生以及高频本质模式函数瞬时频率的波动,改善了Hilbert谱对于高频宽带信号的频率分辨率,使其更加适合复杂多分量的非平稳信号分析。针对水轮机过渡过程中转子振动响应的复杂性和非平稳性,应用该方法对停机和起动过程现场测试信号进行分析,识别了信号的时频结构特征,主轴振动响应主要由转速频率及其谐频成分组成,其中主导成分为转速频率。与Hilbert-Huang变换的对比验证了该方法在分析水轮机过渡过程非平稳振动信号方面的有效性。

Application of Stationary Wavelet Packets Decomposition Based Hilbert Spectrum to Nonstationary Hydraulic Turbine Vibration Signal Analysis

The multi-band decomposition based on stationary wavelet packets transform avoids the defects inherent with Hilbert-Huang transform,such as the pseudo mode functions from empirical mode decomposition and the instantaneous frequency ripple of relatively high frequency intrinsic mode functions.The modification of Hilbert spectrum via stationary wavelet packets decomposition improves its resolution in analyzing the high frequency wide band signals,and enables it more suitable to process the complicated multi-component nonstationary signals.It is employed to analyze the nonstationary vibration signal of a hydroturbine during the shut-down and start-up transient processes.It is found that the main shaft vibration is mainly composed of the rotating frequency and its harmonics,and the rotating frequency is dominant.The comparison with Hilbert-Huang transform verifies its feasibility and effectiveness in analyzing the nonstationary vibration signals of hydroturbine during transient processes.