小波去噪和数据融合及在线监测系统中的应用

准确测量电力设备的各种运行参数,是电力设备在线监测系统进行故障诊断的重要前提,为了从被噪声干扰的各个传感器测量中获得更准确的测量结果,文中提出了一种基于小波去噪和数据融合的多传感器数据重建算法,数据重建的结果更精确地描述原信号,且算法具有计算量少、速度快等特点,并首次将红外测温仪应用于测量变压器绕组的温度在线监测系统中,现场数据的处理验证了该算法的正确性。

Application Of Data Reconstruction Algorithm To Power Apparatus On-line Monition Based on Wavelet Denoising and Data Fusion

It is an important premise for power apparatus fault diagnosis by on- line monitoring system to accurately measure the operating parameters of power apparatus.In order to let each sensor of the multi- sensor system obtain more accurate measurement re- sults,the wavelet- based denoising and the multi- sensor data fusion algorithms are employed to reconstruct outputs of each senor. The results of data reconstruction algorithm are more accurately,and possesses the feature such as less calculation amount and high calcu- lation speed. The first application of infrared temperature measurement to power transformer windings, the correctness of this algorithm is verified by the processing results of on- site data of temperature.