基于紫外光信号的高压电气设备放电检测研究

发布时间：2018-12-13 23:27

【摘要】：随着近年来国民经济的快速发展,整个社会对能源特别是电力方面的需求越来越大。电力设备在制造、运输、安装和运行中不可避免受到电场、热场、机械应力、化学腐蚀以及环境条件等因素的影响,导致绝缘系统的破坏,设备产生局部放电现象。据统计,我国电网中由于电气设备故障而直接引发的电网事故约占事故总量的1/3,仅仅比雷电灾害少,而放电是造成电力设备绝缘系统恶化的主要因素,因此若能对高压设备放电做到早发现、早处理,准确定位放电位置,对提高电网的安全稳定运行具有十分重要的意义。论文对高压设备的放电辐射机理进行了详细的论述,并总结分析了高压设备的放电特征,基于此又对目前国内外高压电气设备放电检测的方法进行了对比分析,总结归纳为电测法和非电测法,主要包括脉冲电流法、超声波法、红外成像法、超高频法、基于紫外光信号法等。电测法容易受到一些电力磁场干扰,灵敏度低等缺点。论文在分析了高压设备放电光谱特征之后,提出了基于日盲型紫外传感器的紫外脉冲法的非电测法来进行放电检测,有效避免了电力磁场干扰,同时也排除了太阳辐射等为外界光线干扰。论文设计了放电检测系统,硬件系统主要包括基于光电倍增管(PMT)R7154日盲紫外传感器的工作电路、信号处理电路(包括I/U转换、增益放大等)、数据采集卡USB_DAQ_PIC16F877_VO5对放电检测数据进行采集和存储电路、温湿度采集电路(分别利用温度传感器DS18B20、湿度传感器DHT11来实现温度和湿度的采集)、模拟高压设备放电及控制装置等,并设计了检测装置工作平台。针对各个硬件模块设计了相应的软件部分来完成各自的功能,采用LABVIEW、MATLAB等软件来实现数据采集、存储、处理,并设计了简单的用户界面。论文在实验室模拟了高压设备放电来对系统的有效性进行了测试,结果表明该系统能够有效地检测高压设备放电情况,具有较好的灵敏度和准确性,并对光信号与放电信号之间的关系进行了探讨,达到了预期目标。
[Abstract]:With the rapid development of national economy in recent years, the whole society needs more and more energy, especially electricity. Electric power equipment is inevitably affected by electric field, thermal field, mechanical stress, chemical corrosion and environmental conditions in manufacture, transportation, installation and operation, which leads to the destruction of insulation system and partial discharge of equipment. According to statistics, the electric network accidents directly caused by electrical equipment failures in our country account for about 1 / 3 of the total number of accidents, only less than lightning disasters, and discharge is the main factor that causes the deterioration of electrical equipment insulation system. Therefore, it is of great significance to improve the safe and stable operation of the power network if the discharge of high-voltage equipment can be detected early, processed early, and accurately located. In this paper, the discharge radiation mechanism of high voltage equipment is discussed in detail, and the discharge characteristics of high voltage equipment are summarized and analyzed. Based on this, the discharge detection methods of high voltage electrical equipment at home and abroad are compared and analyzed. It includes pulse current method, ultrasonic method, infrared imaging method, ultra-high frequency method, ultraviolet light signal method and so on. The electric measurement method is easy to be interfered by some electric magnetic field, and its sensitivity is low. After analyzing the characteristics of discharge spectrum of high-voltage equipment, a non-electric method based on ultraviolet pulse method based on solar blind ultraviolet sensor is proposed to detect the discharge, which effectively avoids the interference of electric magnetic field. At the same time also excluded the solar radiation and other external light interference. In this paper, a discharge detection system is designed. The hardware system mainly includes the working circuit based on photomultiplier tube (PMT) R7154 blind ultraviolet sensor, the signal processing circuit (including I / U conversion, gain amplification and so on). The data acquisition card (USB_DAQ_PIC16F877_VO5) collects and stores the discharge detection data, and the temperature and humidity acquisition circuit (using the temperature sensor DS18B20, humidity sensor DHT11 respectively to realize the temperature and humidity acquisition), The discharge and control devices of high voltage equipment are simulated, and the working platform of detection device is designed. The corresponding software is designed for each hardware module to complete their respective functions. LABVIEW,MATLAB and other software are used to achieve data acquisition, storage, processing, and a simple user interface is designed. This paper simulates the discharge of high-voltage equipment in laboratory to test the effectiveness of the system. The results show that the system can effectively detect the discharge of high-voltage equipment, and has good sensitivity and accuracy. The relationship between the optical signal and the discharge signal is discussed and the expected goal is achieved.
【学位授予单位】：重庆大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TM83;TN23

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