电力变压器绕组状态在线监测关键问题研究

项目名称： 电力变压器绕组状态在线监测关键问题研究

项目编号： No.51207090

项目类型： 青年科学基金项目

立项/批准年度： 2013

项目学科： 电气科学与工程学科

项目作者： 王丰华

作者单位： 上海交通大学

项目金额： 25万元

中文摘要： 振动分析法在线监测变压器绕组状态时，突发短路时变压器绕组振动特性的理论研究和振动信号的特征量提取方法是关键。首先使用电磁暂态软件EMTP和有限元软件ANSYS通过建模研究突发短路时的绕组电动力分布，进而分别建立计及动态短路电动力与垫块非线性的变压器绕组轴向振动多自由度模型和可对变压器绕组变形典型故障进行预设的有限元模型，研究突发短路时变压器绕组振动特性规律。然后分别在时域采用数学形态学与多重分形和在时频域采用局域均值分解法对突发短路时的变压器振动信号进行分析，据此定义时频域特征指数描述突发短路时变压器绕组发生变形乃至损坏演变过程中的振动特性。根据变压器在线监测系统提供的海量电压电流和振动监测数据，提出使用网格密度聚类分析法和自回归广义神经网络法对变压器正常运行时振动信号进行监测和预测。最后，应用分层次模糊综合评判法对变压器绕组状态进行评估，为基于振动分析法的变压器绕组状态监测研究奠定基础。

中文关键词： 变压器；振动信号；电磁场-机械场计算模型；状态检测；优化GRNN

英文摘要： When vibration analysis method is applied to on-line monitor the winding conditions of power transformer, it is important to carry out the theoretical researches of winding vibration characteristics and to extract the features of vibration signal of power transformer under sudden short-circuit impulse. First, the simulated model of power transformer is established under the environment of electromagnetic transient simulation software EMTP and finite element analysis software ANSYS to obtain the distributions of winding electrodynamic force. Then the winding axial vibration multi-freedom model is constructed with the nonlinear effects of insulated block considered based on the previous calculated results of dynamic electrodynamic force to obtain the motion laws of transformer winding. Meanwhile, the three-dimension finine element model of winding is bulit to study the winding vibration varied patterns with preset typical winding deformation or looseness faults. Then the mathematics morphology and multi-fractral analysis methods are selected in time domain and the local mean decomposition method is applied in frequency domain to analysize the vibration signals of power transformer under the sudden short-circuit impulse experiment. Consequently, the time and frequency domain indexes are defined and calculated

英文关键词： power transformer；vibration signal；electromagnetic-mechanical filel model；condition monitoring；optimized GRNN