电力系统自动化2012，Vol.36Issue(2)：31-35,105,6.
稳态和动态混合信号的在线低频振荡模式辨识方法
An Online Low Frequency Oscillation Estimation Method for Ringdown Signals Mixed Ambient Ones
摘要
Abstract
It is well known that it is difficult to achieve disturbance-detecting and algorithm switching in autoregressive moving average （ARMA） method combined with Prony method. A new method is proposed to solve this difficulty. The method is based on normalization kurtosis to judge whether ringdown signal exists in the sliding window. With this method, a low frequency identification scheme is developed to achieve adaptive switching between the common ARMA method and the higher order ARMA method. Case studies are given to compare the performances of the proposed method with Prony method as well as normal ARMA method. The results demonstrate the validity of the proposed scheme.关键词
低频振荡/振荡模式/在线辨识/高阶自回归滑动平均法/超高斯信号/归一化峰度Key words
low frequency oscillation/oscillation mode/online estimation/higher order autoregressive moving average （ARMA） method/super-Gaussian signal/normalization kurtosis分类
信息技术与安全科学引用本文复制引用
徐玉韬,卢继平,陈刚,刘贵富,王予疆,何潜..稳态和动态混合信号的在线低频振荡模式辨识方法[J].电力系统自动化,2012,36(2):31-35,105,6.基金项目
国家重点基础研究发展计划（973计划）资助项目 （）
高等学校学科创新引智计划（“111计划”）资助项目 （）
重庆电力公司科技项目 （）
已申请国家发明专利（申请号：201110208880.8）. （）
