基于加窗的CWT灰度矩提取水电机组非平稳征兆  

Extraction of non-stationary vibration symptoms for hydraulic turbine using improved CWT gray moment with time-scale window

作　　者：陈喜阳[1] 陶迎[1] 闫海桥 张克危[1] 

机构地区：[1]华中科技大学能源与动力工程学院,武汉430074

出　　处：《水力发电学报》2015年第4期152-156,共5页Journal of Hydroelectric Engineering

基　　金：中央高校基本科研业务费专项资金资助(2013);华中科技大学自主创新研究基金项目(0118120050)

摘　　要：针对非平稳信号中特征分量对应的连续小波变换(continuous wavelet transform,CWT)系数在时间-尺度平面集结为高幅值能量区,构建了一种沿时间-尺度方向加窗的CWT灰度矩,蕴含了CWT系数图像的纹理特征,可成为一个量化征兆描述非平稳信号的时频特征。仿真结果表明,时间-尺度加窗CWT灰度矩能有效的提取非平稳信号中突变分量的时间-频率-幅值信息,并应用到了三峡电厂机组的振动分析实例,获得了非平稳信号的时频信息,为水轮机振动量化征兆获取增加了一个新选择。Coefficients of continuous wavelet transform （CWT） of the characteristic components of a non-stationary signal can be assembled for high-amplitude energy region in time-scale plane. An improved CWT gray moment with time-scale window is constructed in this paper to represent the information implicated by a CWT coefficient figure and it can be used as a quantitative time-frequency symptom of the signal. Simulation results show that this method captures effectively the time-frequency amplitudes of mutations components and its successful application to vibration analysis on the hydraulic turbines at the Three Gorges hydropower station has produced useful time-frequency information of non-stationary vibrations. Thus, the CWT method provides a new quantitative approach to extraction of hydraulic turbine vibration symptoms.

关 键 词：水轮机 连续小波变换 非平稳信号 灰度矩 

分 类 号：TM312[电气工程—电机]