【作者】 王婧頔；

【导师】 陈祥献； 黄海；

【作者基本信息】 浙江大学 ， 电子信息技术及仪器， 2010， 硕士

【摘要】 大型电力变压器是电力系统中的重要设备之一,其安全运行对保证电网安全可靠至关重要,实现电力变压器的在线监测和故障诊断意义重大。铁心是变压器的主要部件和故障源之一,其振动主要由硅钢片的磁致伸缩引起,与铁心紧固状况,绝缘程度密切相关,具有较强的非线性非平稳特性。对铁心进行振动特性分析和故障诊断方法实验研究是实现电力变压器在线监测的重要内容。本文以电力变压器铁心为研究对象,将希尔伯特黄变换(HHT)时频分析方法引入变压器铁心非线性振动信号分析领域,结合传统频谱分析法对六种不同型号的电力变压器铁心振动信号进行了分析及实验研究,从时域、频域及时-频域等几个角度分析了铁心本体振动特性、油箱表面空载时振动特性及负载时绕组振动对铁心振动的影响。并在此基础上提出一种基于振动法的电力变压器铁心压紧力在线监测方法。通过对铁心振动信号进行经验模式分解(EEMD),得到一组特征模式函数(IMFs),根据铁心振动特性确定出反映压紧力变化的IMFs,计算IMFs的瞬时频率和时频能量分布,用瞬时频率和时频能量分布构建能够表述铁心压紧力的特征矢量,经距离算法计算特征矢量的长度值,实现铁心压紧力变化的在线监测。实验结果表明,由HHT分析得到的铁心振动时频能量分布清晰地表达出铁心磁致伸缩和电磁力引起的振动过程中铁心瞬时频率及振幅的非线性时变规律。铁心振动信号中包含了丰富的磁化、结构状态以及故障信息。文中提出的特征矢量和距离算法能够有效反映铁心在不同压紧力状况下的振动特性,为电力变压器的振动在线状态监测与故障诊断奠定了良好的基础。更多还原

【Abstract】 Large power transformer is one of the important equipments in the power system.Its safety is essential for ensuring the reliability of power network, which is also of great significance to realize the on-line monitoring and fault diagnosis of power transformer. The transformer core is the main components and also the main fault source. The core vibration, which is produced by magnetostriction and is correlative with the core’s clamping pressure and insulation, is essentially nonlinear and nonstationary. Research on transformer core vibration and fault diagnose is an important part of power transformer on-line monitoring.In this paper, the power transformer core vibration is studied. The new time-frequency analysis method, Hilbert-Huang Transform (HHT) is introduced into transformer core vibration signal analysis. Combing HHT with Fourier transform, six different types of transformer core vibration signal are analyzed on aspect of time-frequency domain. Based on the adaptive HHT technique, we propose a method for analyzing the characteristics of the core vibration. By decomposing the preprocessed vibration signal into a set of intrinsic mode functions (IMFs) through the empirical mode decomposition (EMD), the instantaneous frequencies and the energy-frequency-time distribution of the signal are derived firstly. Then, the instantaneous frequencies and the energy-frequency-time distribution are used to construct a group of eigenvectors to represent the core parameters and a distance algorithm to classify different conditions of the core vibration, based on which the nonlinear and nonstationary characteristics of the core vibration are analyzed.Experimental results show that the derived energy-frequency-time distribution of the core vibration clearly expressed the non-liner time-varying vibration caused by magnetostriction and Electromagnetic force, which contains a wealth of magnetization, structure condition and fault information. The eigenvectors and distance algorithm proposed here can characterize the magnetostriction and pressure of the core effectively. This method is useful and helpful for vibration condition monitoring and diagnosis of power transformers.更多还原