摘要
为了及时有效地诊断变压器绕组松动故障,针对变压器空载合闸振动信号,提出了一种基于变分模态分解(VMD)的分析方法。首先运用VMD对绕组松动前后变压器表面合闸振动信号进行最优模态分解,建立信息熵—峭度—相关系数综合评价模型,并运用熵权—TOPSIS法提取特征模态分量;通过计算变压器振动信号能量熵进一步判定绕组状态;最后搭建测试平台进行实验验证。结果表明,绕组松动和正常状态下变压器振动信号在特征频率和能量分布上均存在明显差异,该方法为变压器绕组松动故障诊断提供了新的思路。
In view of no load closing vibration signal,a kind of analysis based on variational mode decomposition(VMD)is proposed in order to diagnose timely and effectively the looseness of transformer winding.Firstly,the VMD is used to decompose the optimal mode of the closing vibration signal on the transformer surface before and after winding looseness.The comprehensive evaluation model of information entropy⁃kurtosis⁃correlation coefficient is set up and the characteristic modal component is extracted by using entropy weight⁃TOPSIS method.The condition of the winding is determined further by way of calculating the energy entropy of transformer vibration signal.Finally,the test platform is set up for experimental verification.The result shows that the winding looseness and the vibration signal of the transformer under normal condition have significant difference in characteristic frequency and energy distribution.The method provides new idea for diagnosis of looseness of transformer winding.
作者
张九思
马宏忠
李勇
许洪华
朱昊
ZHANG Jiusi;MA Hongzhong;LI Yong;XU Honghua;ZHU Hao(College of Energy and Electrical Engineering,Hohai University,Nanjing 211100,China;State Grid Jiangsu Electric Power Co.,Ltd.Nanjing Power Supply Branch,Nanjing 210019,China)
出处
《高压电器》
CAS
CSCD
北大核心
2021年第8期198-208,共11页
High Voltage Apparatus
基金
国网江苏省电力有限公司重点科技项目资助(J20200042)。
关键词
变压器
变分模态分解
评价模型
能量熵
松动诊断
transformer
variational mode decomposition
evaluation model
energy entropy
looseness diagnosis
