摘要
连续小波变换(CWT)能有效地对水电机组非平稳信号进行细化分析,经过CWT后,蕴涵的状态信息能够在尺度域很好地体现出来,通过小波系数图像素的亮度可分析各个频率成分所占能量比例,引入的灰度矩可体现系数图特征,实例计算验证了灰度矩可作为一个蕴涵机组振动特征的征兆量,可定量地对机组振动情况进行评价,为水电机组分析诊断提供了一种新的征兆量。
Since non-stationary signal of hydro-power unit can be analyzed in details by use of continuous wavelet transform （CWT）, implicated information about the operational status can be extracted in the scale domain using the CWT. Power rate of each frequency is proposed to be refined to deal with the CWT coefficient figure＇ s pixel brightness. Gray moment is then introduced to quantitatively indicate the characteristics of the CWT coefficient figure. It is demonstrated in the paper that the gray moment is effective to be a hydro-power unit vibration symptom for the hydro-power unit analysis and diagnosis.
出处
《电力系统自动化》
EI
CSCD
北大核心
2007年第9期68-71,共4页
Automation of Electric Power Systems
基金
南瑞集团博士后项目(NARI-2006-2)~~
关键词
水电机组
振动
征兆
连续小波变换
灰度矩
hydro-power unit
vibration
symptom
continuous wavelet transform
gray moment
