基于EEMD和近似熵的水电机组摆度去噪方法

提出基于EEMD和近似熵的水电机组摆度信号去噪方法,将信号进行EEMD分解,得到若干个经验模态分量(intrinsic mode function,IMF),求各分量的近似熵,根据预设的近似熵阈值重构经验模态分量,实现水电机组摆度信号的去噪。分别用小波变换(Wavelet)和EEMD处理含噪水电机组摆度信号,比较它们的均方根误差、相关系数和信噪比。结果表明:基于EEMD和近似熵的去噪过程具有自适应性、有很好的去噪性能,非常适合水电机组摆度信号的在线去噪。

De-noising of hydropower unit throw based on EEMD and approximate entropy

A de-noising method of hydropower unit throw signals based on ensemble empirical mode decomposition (EEMD) and approximate entropy is presented. This method decomposes the throw signals into several intrinsic mode functions (IMFs) and calculates the approximate entropy for each function. Those functions of approximate entropy less than a certain preset threshold, then are reconstructed so as to eliminate the abnormal noises of the signals. It also compares the two methods of wavelet transform and EEMD in terms of their calculations of root mean square error, correlation coefficient, and signal-to-noise ratio. The results show that the EEMD method is superior in its adaptability and de-noising performance and very suitable for online de-noising of hydropower unit throw signals.