摘要
针对传统故障行波灰色残差修正组合预测算法存在行波检测性能较差的问题,设计一种基于时域特征的故障行波灰色残差修正组合预测算法,对故障行波数据实施预处理,包括数据平滑处理、归一化处理、空穴填补、平稳化处理、失真数据查找与修正,利用处理后的故障行波数据,基于故障行波的时域特征对故障行波实施故障行波波形变化跟踪,通过TEO能量算子实现波形变化跟踪,根据故障行波波形变化跟踪结果,构建故障行波灰色残差修正模型,实现故障行波灰色残差修正组合预测算法。仿真实验结果证明,该算法的行波检测性能优于传统算法,实现了传统算法的性能突破。
In view of the poor performance of the traditional fault traveling wave gray residual correction combined prediction algorithm,a fault traveling wave gray residual correction combined prediction algorithm based on the time-domain characteristics is designed to preprocess the fault traveling wave data,including data smooth processing,normalization processing,hole filling,smoothing processing,distortion data search and correction after processing the data of fault traveling wave,the waveform change of fault traveling wave is tracked based on the time-domain characteristics of fault traveling wave,and the waveform change is tracked by TEO energy operator.According to the waveform change tracking results of fault traveling wave,the gray residual correction model of fault traveling wave is constructed to realize the combined prediction algorithm of gray residual correction of fault traveling wave.The experimental results show that the traveling wave detection performance of the algorithm is better than the traditional algorithm,and the performance of the traditional algorithm is achieved.
作者
王大勇
WANG Da-yong(Sanmen Nuclear Power Co.,Ltd.,Sanmen 317112,China)
出处
《电子设计工程》
2020年第13期1-4,共4页
Electronic Design Engineering
基金
国家自然科学基金(51805489)。
关键词
时域特征
故障行波
灰色残差修正
组合预测算法
归一化处理
RBF网络
time domain features
fault traveling wave
gray residual correction
eombined prediction algorithm
normalization processing
RBF network