基于EMD和Prony算法的同步电机参数辨识

Parameter Identification of Synchronous Machine Based on Empirical Mode Decomposition and Prony Algorithm

Prony算法是一种线性系统时域模态参数识别方法,对分析数据的噪声非常敏感,对输入信号要求较高。鉴于此,将经验模式分解(empirical mode decomposition,EMD)与Prony算法相结合的方法应用到同步电机参数辨识中。利用EMD的分解能力,对采集到的同步电机三相突然短路电流进行时空滤波和平稳化处理,除去高频噪声IMF分量,然后用Prony准确辨识出同步电机的瞬态和超瞬态参数。仿真试验结果表明该方法具有精度高、抗噪性强等特点。

Prony algorithm is a time-domain modal parameter identification method for linear system, due to its sensitivity to noise in data to be analyzed it puts forward high requirement to input signal. A method combining empirical mode decomposition （EMD） with Prony algorithm was applied to parameter identification of synchronous machines. Using the decomposition ability of EMD, the time-space filtering and stationarization processing were applied to the collected three-phase sudden short-circuit currents of synchronous machine to get rid of intrinsic mode function （IMF） components of high-frequency noise; then transient and subtransient parameters of synchronous machine could be identified accurately by Prony algorithm. Simulation results show that the proposed method possesses advantages of high parameter identification accuracy and strong anti-interference ability.