基于振动信号分析方法的电力变压器状态监测与故障诊断研究
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摘要
振动信号分析方法是一种通过测量和分析变压器箱体表面的振动信号来诊断变压器状态的技术,是对传统电参量监测方法的有力补充。本文以振动信号分析方法作为研究手段,以变压器绕组和铁芯作为研究对象,通过理论分析和试验验证相互结合的方式,对绕组和铁芯正常工作和故障运行时的振动特性进行研究。研究的主要内容包括：绕组和铁芯的受力情况,绕组变形和铁芯压紧状况对其振动的影响,如何准确采集变压器箱体表面的振动信号,箱体表面传感器位置的选择,变压器箱体振动与加载电压和负载电流之间的关系,如何建立箱体振动预测模型,振动预测模型的可扩展性问题,箱体振动信号的特征表示和提取问题等。
围绕上述研究内容,本论文开展的主要研究工作和得出的结论如下所述：
介绍了国内外电力变压器监测与诊断方法的研究现状,重点分析了振动分析方法存在的不足：振动信号特征提取方法存在缺陷,振动预测有限元模型难以准确建立。
论文研究了变压器振动的构成和传播途径,建立了绕组振动的等效数学模型,进行了受力分析,得到绕组振动与绕组压紧状况之间的关系,即绕组位移和变形引起其压紧力变小,引起绕组振动增大；研究引起铁芯振动的磁致伸缩现象及其影响因素。
描述了振动在线监测平台的设计,包括振动传感器的选择、安装,硬件的设计,软件的实现,以及在数据采集时需考虑的干扰问题和相应的抗干扰措施等；对试验用单相变压器和三相电力变压器进行了振动测试,结果显示该振动测试平台满足在线监测的要求；针对三相变压器,进行了油箱表面测点选择的试验研究。此外,研究了不同时刻负载电流的变化规律。
论文根据变压器本体振动产生、传递的机理,以加载电压和负载电流为输入变量,结合机械振动理论,建立了变压器箱体振动预测模型；借助非负线性最小二乘法完成对单相变压器箱体振动模型的参数辨识；利用振动模型预测了某负载和加载电压下的箱体振动,与实测信号进行了比较分析；人为设置了绕组变形故障,利用振动模型进行了初步故障诊断,结果验证了模型的有效性。从振动模型的理论分析基础、输入变量的获取等角度,分析了振动预测模型从单相变压器扩展到三相电力变压器的可行性；结合单相变压器和三相变压器结构方面的异同点,对模型扩展需要考虑的问题进行了探讨,包括温度、有载调压分接开关、冷却方式以及模型时效性等。
总结分析了小波包分析(WPT)在铁芯压紧状况检测中的应用情况及存在的不足；重点针对变压器空载条件下箱体振动(铁芯振动)信号的特点,通过仿真信号进行验证、分析希尔伯特黄变换(HHT)在处理箱体振动信号时出现的问题；据此,提出一种基于小波包变换和希尔伯特黄变换的时间-尺度-频率分析方法。通过计算重构信号与原振动信号之间的平均误差和残差百分比选择合适的小波母函数,利用相关度阈值方法筛选与原信号有更强相关性的频带,借助HHT对小波包处理过的信号进行时间-频率域内的特征表示,将结果与相关文献中的方法进行了比较。利用该方法对铁芯压紧松动故障进行分析和诊断,验证了该方法的有效性。
本文得到安徽省自然科学基金资助(No 070414153)。
Vibration analysis method is the technique to diagnose the conditions of power transformer by measuring and analyzing the vibration signals of its tank, and it is a good supplement for traditional methods based on electrical measurement. In this paper, vibration analysis method is adopted and transformer's core and winding are taken as research objects, their vibration characteristics under normal and unhealthy status are studies by theoretical analysis combined with experimental demonstration. The researches refer to the following aspects:the force analysis for core and winding, the influence on their vibration performances because of winding deformation and core compression condition, how to accurately collect the vibration signals from the surface of power transformer tank, the selection of optimal position of vibration sensors, the relation between vibration signals and applied voltage as well as load current, how to build up vibration prediction model, the expansibility of vibration model, features denotation and extraction for tank vibration signals, etc.
The research is conducted in order to solve the above problems. The main work and conclusions are described as follow:
The research status of monitoring and diagnosis methods for power transformer at home and abroad is introduced. The existing shortcomings in vibration analysis method are analyzed emphatically. Features extraction methods for vibration signals need to be corrected and improved. Besides, current vibration prediction models, which are mostly based on finite element method, are complicated to build up accurately.
The construction and transmission route are studies firstly. The equivalent mathematical model for the winding vibration is proposed and force analysis is conducted. On the basis of force analysis results, the relation between winding vibration and compression situation is investigated in theory. When the compression is degenerate the winding vibration acceleration will enlarge. On the other hand, the principle of core magnetostriction and its influencing factors are presented.
The design process of on-line monitoring platform based on vibration measurement is introduced, such as the selection and fixation of vibration sensors, the design and realization of hardware and software as well as anti-interference treatment. By using the measuring platform, the tank vibration signals are picked up on the surfaces of a single-phase transformer and a three-phase one. The results show that the platform can fulfill the requirements for monitoring the core and winding conditions of power transformer. The research on the optimal position for vibration sensors are carried out on the three-phase transformer. Besides, the changing law of load current at different time is traced.
According to the principles of generation and transmission of transformer vibration, the tank vibration prediction model is proposed using mechanical vibration theory. The parameters identification is completed by non-negative linear least square method, and then the vibration model is utilized to predict the tank vibration under different load and applied voltage while the prediction value is proved to coincide with the measured one. The model is adopted to detect the simulation winding deformation fault, and the results show the validity of the model. Considering the theoretical basis and acquisition of input variables the feasibility of expansibility of tank vibration prediction model, including the influence of temperature, on-load tap-changers vibration as well as timeliness of model, is investigated.
The application of Wavelet Packets Transform (WPT) to monitor the core compression condition is summarized, while the principal shortages are analyzed and pointed out. Considering the characteristics of core vibration signal a simulation signal is constructed for analyzing the intrinsic shortcomings of Hilbert-Huang Transform (HHT) to process tank vibration signals. In order to make use of the advantages and overcome the deficiencies of WPT and HHT, a time-scale-frequency analysis method is developed based on the combination of these two techniques. In this method, the appropriate mother wavelet is established by calculating and quantifying the mean error (ME) and the percent residual difference (PRD) between original signals and reconstructed ones, and then the desirable wavelet packet nodes corresponding to characteristic frequency bands of power transformer are selected through a Correlation Degree Threshold Screening (CDTS) technique, finally HHT is carried out to extract the vibration features in time-frequency domain. The proposed method is used for analyzing and diagnosing the core compression and loosening faults. Compared with the results using the methods in related references, the features obtained by the proposed method reveal clearer condition pattern of the transformer, which shows the potential of this method in condition monitoring of power transformer.
This research is sponsored by Natural Science Foundation of Anhui Province (No.070414153).
围绕上述研究内容,本论文开展的主要研究工作和得出的结论如下所述：
介绍了国内外电力变压器监测与诊断方法的研究现状,重点分析了振动分析方法存在的不足：振动信号特征提取方法存在缺陷,振动预测有限元模型难以准确建立。
论文研究了变压器振动的构成和传播途径,建立了绕组振动的等效数学模型,进行了受力分析,得到绕组振动与绕组压紧状况之间的关系,即绕组位移和变形引起其压紧力变小,引起绕组振动增大；研究引起铁芯振动的磁致伸缩现象及其影响因素。
描述了振动在线监测平台的设计,包括振动传感器的选择、安装,硬件的设计,软件的实现,以及在数据采集时需考虑的干扰问题和相应的抗干扰措施等；对试验用单相变压器和三相电力变压器进行了振动测试,结果显示该振动测试平台满足在线监测的要求；针对三相变压器,进行了油箱表面测点选择的试验研究。此外,研究了不同时刻负载电流的变化规律。
论文根据变压器本体振动产生、传递的机理,以加载电压和负载电流为输入变量,结合机械振动理论,建立了变压器箱体振动预测模型；借助非负线性最小二乘法完成对单相变压器箱体振动模型的参数辨识；利用振动模型预测了某负载和加载电压下的箱体振动,与实测信号进行了比较分析；人为设置了绕组变形故障,利用振动模型进行了初步故障诊断,结果验证了模型的有效性。从振动模型的理论分析基础、输入变量的获取等角度,分析了振动预测模型从单相变压器扩展到三相电力变压器的可行性；结合单相变压器和三相变压器结构方面的异同点,对模型扩展需要考虑的问题进行了探讨,包括温度、有载调压分接开关、冷却方式以及模型时效性等。
总结分析了小波包分析(WPT)在铁芯压紧状况检测中的应用情况及存在的不足；重点针对变压器空载条件下箱体振动(铁芯振动)信号的特点,通过仿真信号进行验证、分析希尔伯特黄变换(HHT)在处理箱体振动信号时出现的问题；据此,提出一种基于小波包变换和希尔伯特黄变换的时间-尺度-频率分析方法。通过计算重构信号与原振动信号之间的平均误差和残差百分比选择合适的小波母函数,利用相关度阈值方法筛选与原信号有更强相关性的频带,借助HHT对小波包处理过的信号进行时间-频率域内的特征表示,将结果与相关文献中的方法进行了比较。利用该方法对铁芯压紧松动故障进行分析和诊断,验证了该方法的有效性。
本文得到安徽省自然科学基金资助(No 070414153)。
Vibration analysis method is the technique to diagnose the conditions of power transformer by measuring and analyzing the vibration signals of its tank, and it is a good supplement for traditional methods based on electrical measurement. In this paper, vibration analysis method is adopted and transformer's core and winding are taken as research objects, their vibration characteristics under normal and unhealthy status are studies by theoretical analysis combined with experimental demonstration. The researches refer to the following aspects:the force analysis for core and winding, the influence on their vibration performances because of winding deformation and core compression condition, how to accurately collect the vibration signals from the surface of power transformer tank, the selection of optimal position of vibration sensors, the relation between vibration signals and applied voltage as well as load current, how to build up vibration prediction model, the expansibility of vibration model, features denotation and extraction for tank vibration signals, etc.
The research is conducted in order to solve the above problems. The main work and conclusions are described as follow:
The research status of monitoring and diagnosis methods for power transformer at home and abroad is introduced. The existing shortcomings in vibration analysis method are analyzed emphatically. Features extraction methods for vibration signals need to be corrected and improved. Besides, current vibration prediction models, which are mostly based on finite element method, are complicated to build up accurately.
The construction and transmission route are studies firstly. The equivalent mathematical model for the winding vibration is proposed and force analysis is conducted. On the basis of force analysis results, the relation between winding vibration and compression situation is investigated in theory. When the compression is degenerate the winding vibration acceleration will enlarge. On the other hand, the principle of core magnetostriction and its influencing factors are presented.
The design process of on-line monitoring platform based on vibration measurement is introduced, such as the selection and fixation of vibration sensors, the design and realization of hardware and software as well as anti-interference treatment. By using the measuring platform, the tank vibration signals are picked up on the surfaces of a single-phase transformer and a three-phase one. The results show that the platform can fulfill the requirements for monitoring the core and winding conditions of power transformer. The research on the optimal position for vibration sensors are carried out on the three-phase transformer. Besides, the changing law of load current at different time is traced.
According to the principles of generation and transmission of transformer vibration, the tank vibration prediction model is proposed using mechanical vibration theory. The parameters identification is completed by non-negative linear least square method, and then the vibration model is utilized to predict the tank vibration under different load and applied voltage while the prediction value is proved to coincide with the measured one. The model is adopted to detect the simulation winding deformation fault, and the results show the validity of the model. Considering the theoretical basis and acquisition of input variables the feasibility of expansibility of tank vibration prediction model, including the influence of temperature, on-load tap-changers vibration as well as timeliness of model, is investigated.
The application of Wavelet Packets Transform (WPT) to monitor the core compression condition is summarized, while the principal shortages are analyzed and pointed out. Considering the characteristics of core vibration signal a simulation signal is constructed for analyzing the intrinsic shortcomings of Hilbert-Huang Transform (HHT) to process tank vibration signals. In order to make use of the advantages and overcome the deficiencies of WPT and HHT, a time-scale-frequency analysis method is developed based on the combination of these two techniques. In this method, the appropriate mother wavelet is established by calculating and quantifying the mean error (ME) and the percent residual difference (PRD) between original signals and reconstructed ones, and then the desirable wavelet packet nodes corresponding to characteristic frequency bands of power transformer are selected through a Correlation Degree Threshold Screening (CDTS) technique, finally HHT is carried out to extract the vibration features in time-frequency domain. The proposed method is used for analyzing and diagnosing the core compression and loosening faults. Compared with the results using the methods in related references, the features obtained by the proposed method reveal clearer condition pattern of the transformer, which shows the potential of this method in condition monitoring of power transformer.
This research is sponsored by Natural Science Foundation of Anhui Province (No.070414153).
引文
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