摘要
采用低门槛突变量启动的行波测距装置记录了故障数据和非故障干扰杂波。然而,行波测距需要的主要信息来自于故障初瞬数据,因此自动筛选出故障初瞬数据是实现行波测距的最基本条件。提出了利用正弦拟合的方法自动筛选故障初瞬数据。将行波测距装置记录的电流行波数据分为两段,分别对这两段数据进行正弦拟合的计算,再根据这两段数据的正弦拟合度和幅值计算数据的模态特征值,若计算得到的数据模态特征值大于设定阈值,则判断其为包含有效信息的故障初瞬数据;反之,则为非故障初瞬数据。大量实测数据计算表明,所提出的输电线路行波测距数据的正弦拟合自动筛选方法是可行的,且准确可靠。
Traveling wave fault location devices record fault data and non-fault interference clutter using low-threshold variation start. However, the main information of traveling wave ranging is from fault early instantaneous data. So the most basic condition of traveling wave ranging is to screen out fault early instantaneous data automatically. This paper proposes a method of sinusoidal fitting to automatically screen out fault early instantaneous data. The current traveling data recorded by traveling wave fault location device is divided into two sections, the sine fitting of two sections is calculated respectively. Then modal eigenvalues of two pieces are calculated according to the degree and amplitude of sine fitting. If the calculated modal eigenvalue is greater than the set threshold value, it is judged as a failure early instantaneous data that contains valid information. On the contrary, it is regarded as the non-fault early instantaneous data. A large number of calculations show that the proposed transmission line traveling wave data automatically screening method based on sine fitting is feasible, accurate and reliable.
出处
《电力系统保护与控制》
EI
CSCD
北大核心
2015年第20期58-64,共7页
Power System Protection and Control
关键词
行波测距
正弦拟合
故障数据
数据模态特征值
自动筛选
traveling wave ranging
sine fitting
fault data
data modal eigenvalue
screening automatically