基于改进多信号Prony算法的低频振荡在线辨识

提出了适合低频振荡在线辨识的改进多信号Prony算法。首先通过小波变换消除各信号的噪声，然后消去直流分量，建立多信号的样本函数矩阵，通过奇异值–总体最小二乘法对Prony算法进行改进，分离信号空间和噪声子空间，确定信号的阶数，最后利用最小二乘法进行辨识。利用传统Prony算法、改进单信号Prony算法和改进多信号Prony算法对理想信号、仿真信号以及实际录波信号进行了分析，分析结果表明利用改进多信号Prony算法同时对多信号进行分析能够提高辨识的精度，缩短运算时间，辨识阶数及辨识结果均优于传统算法，适合于低频振荡的在线辨识。

Online Identification of Low-Frequency Oscillations Based on Improved Multi-Signal Prony Algorithm

An improved multi-signal Prony algorithm suitable to on-line identification of low frequency oscillation is proposed. Firstly, by means of wavelet transform the noise contained in each signal is eliminated; then the DC component is also eliminated and sample function matrix for multi-signal is built up, the Prony algorithm is improved by means of singular value decomposed-total least square (SVD-TLS) and the signal space is separated from noise sub-space, and then the order number of signal is determined; finally, the identification is carried out by least square. The ideal signal, simulated signal and practical recorded signal are analyzed by traditional Prony algorithm, the improved single signal Prony algorithm and the improved multi-signal Prony algorithm respectively, analysis results show that the identification accuracy can be improved while signals are simultaneously analyzed by the proposed improved multi-signal Prony algorithm, the calculation time is reduced, and the identified order number as well as the identified result are in advance of traditional algorithms, so the proposed algorithm is suitable to on-line identification of low frequency oscillation.