水轮机调节系统参数辨识中试验数据的预处理方法

Data Pre-treatment for Parameter Identification of Hydro Turbine Governing System

水轮机调节系统参数辨识现场试验的原始数据往往包含各种干扰信号。为提高辨识的准确性,在应用辨识算法前,需进行数据预处理。为此,探讨对辨识试验数据的预处理的方法,包括信号重采样、去除稳态值、去除趋势和噪声滤波等,并着重分析和给出了采用经验模态分解方法(EMD)对信号进行滤波和去噪的原理和效果。

The raw data of filed test for hydro turbine governing system parameter identification usually contains a variety of interference signals.For improving the accuracy of identification,they should be pretreated before the identification algorithm is applied.The pretreatment methods,including signal re-sampling,steady-state and trend removing and noise filtering,were discussed herein.The principle and effectiveness for signal filtering and de-noising by using empirical mode decomposition(EMD) are analyzed.