基于JADE算法的变压器振动信号分离的研究

Research on Vibration Signal Separation of Transformer Based on JADE Algorithm

为了实现变压器绕组和铁心振动信号的分离,从而达到对绕组与铁心运行状态监测的目的,文章利用独立分量分析理论(ICA)与联合近似对角化算法(JADE),将变压器铁心、绕组的振动信号从传感器监测到的混合信号中分离出来,并根据各个部件振动信号与数据库原始信号中的频率特性对比分析,判断变压器的故障隐患。采用LabVIEW与MATLAB混合编程技术对JADE算法进行编程,由仿真结果可知:在信号源和混合参数未知的情况下,JADE算法能根据观测信号以及源信号统计独立的假设对源信号进行可靠分离。

The purpose of separating transformer winding signal and the vibration signal of iron core is to monitor their operation status,so in this paper,the vibration signal of transformer iron core and winding is separated from hybrid signals monitored by sensor based on independent component analysis（ICA） theory and Joint Approximate Diagonalization of Eigen-matrices（JADE） algorithm.Then the frequency characteristics of vibration signal of each element are compared and analyzed with original signals from database,which can judge the hidden faults of transformer.The JADE algorithm is realized by combing LabVIEW and MATLAB.Simulation results show that JADE algorithm can be used to separate source signals from monitored signals and source signals under unknown signal source and hybrid parameters.