智能变电站变压器在线监测与故障诊断系统设计

发布时间：2018-02-25 21:18

  本文关键词： 变压器 在线监测 神经网络算法 故障诊断　出处：《西南交通大学》2017年硕士论文　论文类型：学位论文

【摘要】：智能变电站的发展对变压器智能化水平提出了更高的要求,变电站变压器在线监测与故障诊断技术也在逐步改善和提高,变压器智能化水平的提高不仅能提高电网工作人员的效率,更对电力系统的稳定运行起着重要作用。对智能变电站中变压器的运行情况进行实时在线监测,能够及时发现变压器运行过程中的问题,在线故障诊断系统能够预测变压器潜在故障,在变压器发生故障前就及时找出问题,避免由于变压器故障导致的电力系统运行不稳定甚至是停电等造成的危害。基于BP神经网络算法,采用遗传算法优化后作为变压器故障诊断的方法,通过相应的硬件和软件实现,完成了变压器在线监测与故障诊断系统的设计。通过对人工智能诊断方法的研究,提出采用BP神经网络算法作为变压器故障诊断的手段,并基于遗传算法对BP神经网络算法进行优化设计,在Matlab软件平台上对算法做了仿真验证,结果证明,优化后的神经网络算法准确性得到了提高。以LPC2214CPU的ARM芯片为核心,设计了变压器油中气体浓度的数据采集和传输的硬件系统,并将uC/OS-Ⅱ实时操作系统进行移植,结合嵌入式软件系统实现整体功能,基于LabVIEW虚拟仪器软件设计了上位机在线监测系统,通过图形化编程,设计了数据采集与DGA分析模块,基于神经网络的故障诊断模块和数据库模块,完成了变压器在线监测与故障诊断系统的人机交互操作界面设计。本文所设计的变压器在线监测与故障诊断系统,不仅完成了基于遗传算法改进后的BP神经网络算法的理论验证,并且在分析实际需求的基础上,通过嵌入式系统对硬件和软件部分设计实现了具体的数据采集、信息传输、在线监测、故障诊断、数据库存储等功能,完成了变压器在线监测与故障诊断系统的设计,为变压器在线监测与人工智能诊断的实际应用提供了具体的解决方案。
[Abstract]:The development of intelligent substation puts forward higher requirements for the level of transformer intelligence, and the on-line monitoring and fault diagnosis technology of transformer in substation is also gradually improved and improved. The improvement of transformer intelligence level can not only improve the efficiency of power grid workers, but also play an important role in the stable operation of power system. The on-line fault diagnosis system can predict the potential fault of the transformer and find out the problem before the fault of the transformer occurs. Based on BP neural network algorithm, genetic algorithm is adopted as the method of transformer fault diagnosis. Through the realization of corresponding hardware and software, the design of transformer on-line monitoring and fault diagnosis system is completed. Through the research of artificial intelligence diagnosis method, BP neural network algorithm is used as the means of transformer fault diagnosis. The BP neural network algorithm is optimized based on genetic algorithm, and the algorithm is simulated on the Matlab software platform. The results show that the accuracy of the optimized neural network algorithm has been improved. The core of this algorithm is the ARM chip of LPC2214CPU. The hardware system of data acquisition and transmission of gas concentration in transformer oil is designed, and the UC / OS- 鈪，

本文编号：1535180