基于EMD和卡尔曼滤波的振荡信号检测.doc

基于EMD和卡尔曼滤波的振荡信号检测 许峰，李开成，王可 （华中科技大学 强电磁工程与新技术国家重点实验室） ：针对振荡信号计算振荡信号的参数同时定位发生的时刻随机性使常常叠加基波信号之上EMD分解将叠加基波信号上的振荡出来，使可靠卡尔曼状态空间时，利用Z变迭代关系，使得指数的信号状态更新变得简单方法精确地检测出振荡的频率和衰减指数，最后用发生起始点的采样值振荡最大幅值卡尔曼容纳一定程度的噪声，卡尔曼滤波将噪声的影响有效降低，仿真实验可以看到方法能有效振荡信号的参数，确定振荡有效区间，误差均较小。最后比较振荡信号的方法，证明了本方法的优势。：EMD卡尔曼滤波; 振荡TM714 文献标识码：A 文章编号：1001－1390（2015）24－0000－00 The detection of oscillation signal based on EMD and Kalman filter Xu Feng, Li Kaicheng, Wang Ke (State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, Wuhan 430074, China) Abstract: The method proposed in this paper aims to detect parameters of oscillation signal and locate the fault. Oscillation is often superimposed on the fundamental frequency signal for its randomness, and EMD can extract it, thus making Kalman state-space model more simply and reliable. When we establish the Kalman state space, the use of Z-transform makes its state updates easier. The proposed method can measure frequency and damping factor of oscillation precisely and quickly. Finally, the sample values of the starting point of the oscillation helps to determine the maximum amplitude of the oscillation quickly. Kalman filter allows some degree of noise, which can reduce influence of noise effectively. The simulation results can be seen that the method can detect oscillation real-time parameter efficiently and locate the oscillation range, and all of its error is acceptable. Compared with several oscillation detecting methods, the algorithm proposed in this paper was proved to be advantageous. Keywords: EMD, Kalman filter, oscillation detection 0 引 言 中和配电网中，经常由于各种不同事件引起低频振荡，其中最常见的是电容器组的合闸。一般振荡的小于5kHz，时间在ms~50ms之间。暂态振荡会导致电子设备的损坏振荡参数的检测是治理扰动的[1]提出了一种扩展卡尔曼滤波方法追踪系统振荡，跟踪多成分的信号了传统滤波的精度但是该方法建立的状态空间含有指数部分，状态传输矩阵乘数项变得，迭代时间变2]将Z变换到卡尔曼状态空间方程的建立中，用模糊控制调节过程，检测出闪变参数，了运算效率Prony方法被广泛低频振荡辨识能够根据采样值直接估算出信号频率、衰减和幅值。该方法采用的数学模型一组多个具有任意幅值、相位、频率和衰减因子的指数函数，需要整个频域范围内待采样函数，计算效率不高对噪声敏感需判断信号发生的时刻。 基于E