基于数字化变电站的电力设备故障诊断研究
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摘要
电力设备在整个数字化变电站的运行当中有着重要的地位。随着科学技术的发展和人民生活水平的提高,不仅对用电质量,也对电力设备的安全运行提出了更高的要求。特别是当前,电力系统的发展方向就是大容量、超高压,这就意味着停电事故对生产和生活造成的的损失也越来越大。所以对电力设备的运行状态进行实时在线监测并且对其进行故障诊断是十分必要和重要的。
根据数字化变电站的发展情况和IEC61850规约的内容,本文介绍了基于IEC61850的数字化变电站的组成和结构特点,简单地阐述了智能化一次设备的概念,深入研究了部分智能一次设备的功能结构和原理,并对智能一次设备发展目标进行了总结。在此基础上,本文着重对各种智能化一次设备的在线监测装置、故障量的采集及提取和故障诊断方法进行了深入的研究。
随着计算机技术、传感器技术和信息技术的发展,数字化变电站中可以对智能化一次设备进行不同故障特征量的同时在线监测和故障诊断。在本文中,针对断路器和变压器等智能一次设备的故障特点,在充分考虑故障诊断的可靠性的前提下,同时对多种故障特征信息进行实时在线监测和故障诊断,并且对依据各种特征量的诊断结果进行汇总后,利用模糊理论对诊断结果进行总体分析,对故障进一步深入的诊断,这样做可以大大提高故障诊断的准确率。
在断路器振动信号故障量的提取时,目前大部分的文献提到的方法都是将时间能量特征作为唯一的特征量,虽然这样选取的特征量包含了大部分的故障信息,但是包含在时间频率中的故障信息被遗漏掉了,所以本文在希尔伯特变换-黄变换的基础上,提出了将时间频率的特征加入到特征量中,使得诊断系统所得到的特征量中包含了更多的故障信息,提高了故障诊断的准确率。
在电力设备故障诊断中,人工智能和专家系统的引入是一个亮点。本文对数字化变电站中电力设备故障诊断的专家系统进行了详细的阐述和深入研究,提出了种新型的基于WEB的故障诊断专家系统。最后本文对基于WEB的故障诊断专家系统在数字化变电中的硬件和软件的实现做了深入的研究。
通过本文的研究可以肯定,基于WEB的电力设备故障诊断专家系统在数字化变电站中有着诸多优点,是以后数字化变电站网络化和智能化的一个重要组成部分。
Power equipment plays an important role in the operation of the digital substation. With the development of science and technology and the improvement of living standards, not only the quality of electricity, but also the safe operation of power equipment, has put forward higher requirements. Especially in the current, the direction of the power system 's development is the large capacity and extra-high voltage, which means the damage of the production and living, caused by blackouts, is also growing. Therefore, real-time and on-line monitoring of power equipment's condition and fault diagnosis of power equipment is very necessary and important.
Based on the development of digital substation and the IEC61850,this paper introduces the composition and structure of the digital substation based on IEC61850, and simply illustrates of the intelligent primary equipment. Also, this paper studies in depth the function structure and principle of the intelligent primary equipment, and summarizes the development goals of the intelligent primary equipment. On this basis, the paper focuses on the on-line monitoring device、the extraction of the characteristic quantities and the method of fault diagnosis.
With the development of computer technology, sensor technology and information technology, we can monitor several characteristic parameters for one intelligent primary equipment at the same time and find it's fault in digital substation. In this paper, based on the fault characteristics of the circuit breaker and transformer and taking the reliability of fault diagnosis of the premise into account, several kinds of feature information are monitored at the same time and the result of the fault diagnosis based on different information will be summarized in a fuzzy expert system to improve the accuracy of fault diagnosis.
Now in terms of the characteristic parameter extraction, many methods take the time-energy as the only characteristic parameter, which contains most fault characteristics, but loses the time-frequency characteristic. So in this paper a new method which includes time-frequency characteristic is used to improve the accuracy of fault diagnosis.
In the field of the power equipment fault diagnosis, the introduction of artificial intelligence and expert systems is a bright spot. In this paper, power equipment fault diagnosis expert system is described in detail, and a new WEB-based expert fault diagnosis system is put forward. Finally, this paper does in-depth study on the hardware and software realization of the WEB-based expert fault diagnosis system.
Through this research, It can be sure that WEB-based power equipment fault diagnosis expert system has many advantages, and it is an important part of the digital networking and intelligent substation.
根据数字化变电站的发展情况和IEC61850规约的内容,本文介绍了基于IEC61850的数字化变电站的组成和结构特点,简单地阐述了智能化一次设备的概念,深入研究了部分智能一次设备的功能结构和原理,并对智能一次设备发展目标进行了总结。在此基础上,本文着重对各种智能化一次设备的在线监测装置、故障量的采集及提取和故障诊断方法进行了深入的研究。
随着计算机技术、传感器技术和信息技术的发展,数字化变电站中可以对智能化一次设备进行不同故障特征量的同时在线监测和故障诊断。在本文中,针对断路器和变压器等智能一次设备的故障特点,在充分考虑故障诊断的可靠性的前提下,同时对多种故障特征信息进行实时在线监测和故障诊断,并且对依据各种特征量的诊断结果进行汇总后,利用模糊理论对诊断结果进行总体分析,对故障进一步深入的诊断,这样做可以大大提高故障诊断的准确率。
在断路器振动信号故障量的提取时,目前大部分的文献提到的方法都是将时间能量特征作为唯一的特征量,虽然这样选取的特征量包含了大部分的故障信息,但是包含在时间频率中的故障信息被遗漏掉了,所以本文在希尔伯特变换-黄变换的基础上,提出了将时间频率的特征加入到特征量中,使得诊断系统所得到的特征量中包含了更多的故障信息,提高了故障诊断的准确率。
在电力设备故障诊断中,人工智能和专家系统的引入是一个亮点。本文对数字化变电站中电力设备故障诊断的专家系统进行了详细的阐述和深入研究,提出了种新型的基于WEB的故障诊断专家系统。最后本文对基于WEB的故障诊断专家系统在数字化变电中的硬件和软件的实现做了深入的研究。
通过本文的研究可以肯定,基于WEB的电力设备故障诊断专家系统在数字化变电站中有着诸多优点,是以后数字化变电站网络化和智能化的一个重要组成部分。
Power equipment plays an important role in the operation of the digital substation. With the development of science and technology and the improvement of living standards, not only the quality of electricity, but also the safe operation of power equipment, has put forward higher requirements. Especially in the current, the direction of the power system 's development is the large capacity and extra-high voltage, which means the damage of the production and living, caused by blackouts, is also growing. Therefore, real-time and on-line monitoring of power equipment's condition and fault diagnosis of power equipment is very necessary and important.
Based on the development of digital substation and the IEC61850,this paper introduces the composition and structure of the digital substation based on IEC61850, and simply illustrates of the intelligent primary equipment. Also, this paper studies in depth the function structure and principle of the intelligent primary equipment, and summarizes the development goals of the intelligent primary equipment. On this basis, the paper focuses on the on-line monitoring device、the extraction of the characteristic quantities and the method of fault diagnosis.
With the development of computer technology, sensor technology and information technology, we can monitor several characteristic parameters for one intelligent primary equipment at the same time and find it's fault in digital substation. In this paper, based on the fault characteristics of the circuit breaker and transformer and taking the reliability of fault diagnosis of the premise into account, several kinds of feature information are monitored at the same time and the result of the fault diagnosis based on different information will be summarized in a fuzzy expert system to improve the accuracy of fault diagnosis.
Now in terms of the characteristic parameter extraction, many methods take the time-energy as the only characteristic parameter, which contains most fault characteristics, but loses the time-frequency characteristic. So in this paper a new method which includes time-frequency characteristic is used to improve the accuracy of fault diagnosis.
In the field of the power equipment fault diagnosis, the introduction of artificial intelligence and expert systems is a bright spot. In this paper, power equipment fault diagnosis expert system is described in detail, and a new WEB-based expert fault diagnosis system is put forward. Finally, this paper does in-depth study on the hardware and software realization of the WEB-based expert fault diagnosis system.
Through this research, It can be sure that WEB-based power equipment fault diagnosis expert system has many advantages, and it is an important part of the digital networking and intelligent substation.
引文
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