基于自适应粒子群算法的变压器局部放电超声定位技术

发布时间：2018-01-23 03:08

  本文关键词： 变压器 局部放电 超声波 定位 粒子群算法　出处：《长沙理工大学》2014年硕士论文　论文类型：学位论文

【摘要】：在电力系统中,大型电力变压器的绝缘状况影响着整个系统的安全稳定运行,变压器产生的故障大部分是由于变压器局部放电所引起的,而变压器绝缘介质的劣化是引起局部放电的主要原因,对绝缘状态主要根据绝缘介质在劣化过程中的一些特征参数来进行评定,包括电容量、泄漏电流、局部放电等,其中局部放电主要反映了绝缘介质的局部状况,在绝缘检测中具有不可替代的作用,因此对变压器局部放电检测和定位也是电力部门的重点工作之一。超声波定位法是局部放电检测和定位的最传统也是最主要的方法,而超声波定位法的关键环节就是定位算法问题。论文对超声波定位法及定位算法做了较深入的研究。论文首先分析了变压器局部放电产生原因及特点,同时对局部放电产生超声波的机理进行研究,并对超声波在变压器内部传播的衰减情况及速度进行测量,为超声波定位提供可靠的依据；其次深入研究了超声定位算法,针对基本粒子群算法存在的缺点对其进行改进,提出了自适应粒子群算法,此算法能很好的克服基本粒子群算法容易陷入局部最优的缺点,并将自适应粒子群算法应用到超声定位中；论文最后建立了超声定位的数学模型,并且将其转化为一种带约束条件的优化问题,然后通过设计的检测系统以及现场检测的数据对变压器局部放电点进行定位。
[Abstract]:In the power system, the insulation condition of the large power transformer affects the safe and stable operation of the whole system. The fault caused by the transformer is mostly caused by the partial discharge of the transformer. The deterioration of insulation medium of transformer is the main cause of partial discharge. The insulation state is mainly assessed according to some characteristic parameters of insulation medium in the process of deterioration, including capacitance, leakage current. Partial discharge, among which partial discharge mainly reflects the partial condition of insulating dielectric, plays an irreplaceable role in insulation detection. Therefore, the detection and location of transformer partial discharge is also one of the key tasks in the power sector. Ultrasonic localization is the most traditional and main method of partial discharge detection and location. The key link of ultrasonic positioning is the localization algorithm. This paper makes a deep research on the ultrasonic positioning method and location algorithm. Firstly, this paper analyzes the causes and characteristics of transformer partial discharge. At the same time, the mechanism of ultrasonic wave produced by partial discharge is studied, and the attenuation and velocity of ultrasonic wave propagation in transformer are measured, which provides a reliable basis for ultrasonic positioning. Secondly, the ultrasonic localization algorithm is deeply studied, and the adaptive particle swarm optimization algorithm is proposed to improve the basic particle swarm optimization algorithm. This algorithm can overcome the shortcoming that the basic particle swarm optimization is easy to fall into local optimum, and the adaptive particle swarm optimization algorithm is applied to ultrasonic localization. At last, the mathematical model of ultrasonic localization is established and transformed into an optimization problem with constraints. Then the partial discharge point of transformer is located by the designed detection system and the field detection data.
【学位授予单位】：长沙理工大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM41
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本文编号：1456528