基于振动信号分析方法的电力变压器状态评估研究

发布时间：2018-06-02 03:22

本文选题：变压器 + 绕组　；参考：《华北电力大学》2017年硕士论文

【摘要】：近年来,我国大量建设特高压变电站,提升电网的电压等级。变压器作为电网的枢纽设备,分析评估其运行健康状况有利于保证电力系统的安全稳定运行。本文理论分析了绕组所受预紧力大小与振动信号加速度间的关系,研究了绕组轴向不同位置处固有频率的分布规律,提出了基于集合经验模态分解和负熵准则的单通道变压器振动信号盲分离方法,并基于振动信号数据对变压器运行健康状况进行评估。主要工作如下:根据绕组轴向振动弹簧质量块模型,分析了绕组所受预紧力大小与振动加速度幅值之间的关系。计及绕组自身重力和安培力稳态分量影响,对绕组线饼单元进行受力分析,得出绕组轴向固有频率的分布规律。通过分析实际运行变压器振动信号数据,验证了理论分析的正确性。提出了基于集合经验模态分解和负熵准则的变压器振动信号盲源分离方法,与传统盲源分离方法相比,其通过信号升维处理将欠定盲源分离问题转化为适定盲源分离问题,实现了从单通道混合振动信号中分离得到各个振动源信号。通过对仿真和实测信号进行分析,并与Fast ICA分离结果进行对比,验证了所提方法的有效性。提出了一种基于多测点振动信号频谱分布特征的变压器状态评估方法。选取频率复杂度和振动信号各频段能量分布百分比作为特征指标,分析变压器振动信号频谱分布特征。通过计算各测点频段能量分布百分比的相关性,评估变压器运行健康状况。
[Abstract]:In recent years, a large number of UHV substations have been built in China to enhance the voltage level of the power grid. Transformer is the hub equipment of power network. It is helpful to ensure the safe and stable operation of power system by analyzing and evaluating its running health. In this paper, the relationship between the magnitude of the pretightening force and the acceleration of the vibration signal is analyzed theoretically, and the distribution of the natural frequency at different positions of the winding is studied. A blind separation method for vibration signals of single-channel transformers based on set empirical mode decomposition and negative entropy criterion is proposed, and the operating health of transformers is evaluated based on vibration signal data. The main work is as follows: according to the mass block model of the axial vibration spring, the relationship between the magnitude of the pretightening force and the amplitude of the vibration acceleration is analyzed. Considering the influence of the steady state component of the winding gravity and ampere force, the distribution of the natural frequency of winding axial direction is obtained by analyzing the force of the winding wire-cake unit. The correctness of the theoretical analysis is verified by analyzing the vibration signal data of the actual operating transformer. A blind source separation method for transformer vibration signal based on set empirical mode decomposition and negative entropy criterion is proposed. Compared with the traditional blind source separation method, the problem of under-determined blind source separation is transformed into a suitable blind source separation problem by signal dimension raising processing. Each vibration source signal can be separated from the single channel mixed vibration signal. The effectiveness of the proposed method is verified by analyzing the simulated and measured signals and comparing with the Fast ICA separation results. In this paper, a method for evaluating transformer state based on the spectrum distribution of vibration signals at multiple measurement points is presented. The frequency complexity and the percentage of energy distribution in each frequency band of the vibration signal are selected as the characteristic indexes to analyze the spectrum distribution characteristics of the transformer vibration signal. By calculating the correlation of the percentage of energy distribution in each measuring point, the operating health of transformer is evaluated.
【学位授予单位】：华北电力大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM41

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