基于形态滤波和Prony算法的低频振荡模式辨识的研究

Research on identifying low frequency oscillation modes based on morphological filtering theory and Prony algorithm

针对传统Prony方法对噪声敏感导致辨识精度不高的问题,提出了一种基于形态滤波和Prony算法相结合的低频振荡模式辨识的方法,实现了在有混合噪声干扰情况下低频振荡模式的准确辨识。基于数学形态学,设计了一种基于半圆形结构元素的形态滤波器,在选取合适的元素尺寸情况下,可以有效滤除混合噪声。对于去噪声之后的信号采用Prony算法进行辨识,可准确获取低频振荡各个模式参数。通过Matlab进行算例仿真,表明了对电力信号进行预处理的必要性以及所提出的方法能相对精确地进行振荡模式辨识,验证了其有效性。

A method based on morphological filtering theory and power algorithm is put forward to identify low frequency oscillation modes, aiming at how to avoid the limitation of Prony methods that is sensitive to noise thus to cause the inaccuracy. It realizes accurate identification of oscillation modes in the condition of fixed noises. A morphology filter, which is based on mathematical morphology and hemicycle structure element is designed to effectively suppress the noise in the condition of proper size of the element. Prony algorithm is then used to detect the de-noised signal and obtain the low frequency oscillation parameters of every mode. The Matlab simulation results show that it is very necessary to preprocess the data of electric signal. Effectiveness and relatively accuracy are verified.