摘要
在对低频振荡信号特征参数的提取过程中往往会存在噪声干扰和辨识算法定阶不准确的问题。针对此问题,提出了Stein的无偏似然估计(SURE)小波阈值消噪和总体最小二乘-旋转不变技术(TLS-ESPRIT)相结合的方法,用于提取振荡模态的参数。首先利用SURE小波阈值消噪技术实现对振荡信号的预处理,提升信号的信噪比,而后将处理后的信号作为新的主导信号利用TLS-ESPRIT算法进行振荡参数的辨识。在辨识算法的关键定阶问题上,提出的归一化奇异熵的定阶方法能使信号模态阶数的估计值更加接近真实值。通过对数值信号算例和PSASP中EPRI8机36节点系统算例进行仿真,并与传统算法进行对比,验证了该改进方法的可行性和精确性。
In the extraction of modal parameters of low-frequency oscillation signals,there are often problems such as noise interference and inaccurate identification algorithm.To solve this problem,a method combining SURE wavelet threshold denoising with TLS-ESPRIT is proposed to extract the parameters of oscillation modes.Firstly,the SURE wavelet threshold denoising technology is used to preprocess the oscillation signal and improve the signal-to-noise ratio of the signal,and then the processed signal is used as the new dominant signal to identify the oscillation parameters by TLS-ESPRIT algorithm.On the key problem of identification algorithm,the order determination method of normalized singular entropy is proposed,which can make the estimated value of signal modal order closer to the real value.The feasibility and accuracy of the improved method are verified by simulation of numerical signal examples and EPRI836-bus system examples in PSASP,and compared with the traditional algorithm.
作者
陈昱升
李培强
张斓
CHEN Yu-sheng;LI Pei-qiang;ZHANG Lan(School of Electronic,Electrical and Physics,Fujian University of Technology,Fuzhou 350118,China)
出处
《电气开关》
2023年第1期84-89,96,共7页
Electric Switchgear
