基于敏感IMFs的变压器振动信号盲分离

Zhen Li, Qingshuai Ren, Jing Ding, Renjie Wang, Ping Ju, Qingquan Li
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引用次数: 0

摘要

从变压器油箱壁面测得的振动信号是多种振动源信号的混合,变压器振动信号的特征提取和故障诊断比较困难。针对单通道变压器振动信号难以分离的问题,提出了一种基于敏感IMF的变压器振动信号盲分离方法。首先对变压器振动特性进行分析,然后对变分模态分解(VMD)算法分解的内禀模态函数(IMF)进行筛选,并基于敏感因子进行重构。将VMD算法与快速独立分量分析(FastICA)算法相结合,分离振动信号。根据变压器振动特性构造仿真信号对该方法进行了验证,并将该方法应用于变压器振动信号的分离,验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Blind Separation of Transformer Vibration Signal Based on Sensitive IMFs
The vibration signal measured from the wall of the transformer oil tank is a mixture of various vibration source signals, and it is difficult to extract the characteristics of the transformer vibration signal and fault diagnosis. In this paper, a blind separation method of transformer vibration signal based on sensitive IMF is proposed aiming at the problem that the single-channel transformer vibration signal is difficult to separate. First, this paper analyzes the transformer vibration characteristics, and then the Intrinsic Mode Function (IMF) decomposed by the Variational Mode Decomposition (VMD) algorithm is screened and reconstructed based on the sensitive factor. The VMD algorithm is combined with the Fast Independent Component Analysis (FastICA) algorithm to separate the vibration signal. The method is verified by constructing a simulation signal according to the transformer vibration characteristics, and the method is applied to separate the transformer vibration signal to prove the effectiveness of the method.
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