摘要
电力系统的安全运行与其枢纽设备变压器的可靠性直接相关,因此变压器的状态检修是必不可少的。在实行状态检修时,需要对变压器的运行状态做出精确评估,变压器内部故障程度是决定是否需要检修的一个重要标准。本文通过模拟变压器的匝间故障,获取故障状态下的一次电流信号,采用基于符号动力学的方法符号化电流数据,建立信号差异测量机制对数据进行分析。仿真表明在匝间阻抗下降时,该方法可有效地检测出故障信号与正常工作信号的差异,为状态检修提供了坚实依据。在此基础上,本文在变压器内部故障的现场数据上进行了同样的分析,证实了符号动力学在检测变压器内部故障上的有效性。
The safe running of power system is directly related to the reliability of its core equipment transformer. As the result, condition based maintenance of transformers is essential. When implementing the condition based maintenance, it is necessary to give an accurate state assessment of the transformer which decides whether the transformer need to be rep.aired. This paper simulates the inter-turn fault of the transformer in order to gain the primary side current data under this condition. Then symbolic dynamic is used to generate a sequence of symbols from the current data and set up the mechanism of signal difference measurement to analyze the data. Results of simulation shows that when the inter-turn impedance becomes lower the method can effectively recognize the difference between the normal and fault signal, which provides asolid foundation of the condition based maintenance. Moreover this paper test the symbolic dynamic method on the field test data of transformer internal fault, the result verifies the validity of the symbolic dynamic on the detection of transform internal fault.
出处
《电工技术学报》
EI
CSCD
北大核心
2015年第20期57-64,共8页
Transactions of China Electrotechnical Society
基金
国家杰出青年科学基金(50925727)
湖南省科技计划(2010FJ3035)资助项目
关键词
符号动力学
变压器内部故障
状态检修
最大熵划分
Symbolic dynamic, transform internal fault, condition based maintenance, maximum entropy based partitioning
