高电压技术2018，Vol.44Issue(8)：2457-2463,7.DOI:10.13336/j.1003-6520.hve.20180731004
用ILMD多尺度时频熵识别直流牵引网振荡电流与故障电流
Identification Approach of Oscillation Current and Fault Current in DC Traction Network Based on ILMD Multi-Scale Time-Frequency Entropy
摘要
Abstract
Aiming at frequent malfunctions of the relay protection system caused by the oscillation current in DC traction network of urban rail transit, we propose a method for identifying the oscillation current and short-circuit fault current in DC traction network based on improved local mean decomposition (ILMD) and multi-scale time-frequency entropy. Firstly, the ILMD method is used to analyze the feeder current signal in DC traction network so that the time-frequency distribution of the feeder current signal can be obtained. Secondly, the Shannon entropy theory is introduced into the time-frequency distribution, and the time-frequency plane is divided into some frequency channels. Then the time-frequency entropy of each frequency channel is figured out. Finally, the overall multi-scale time-frequency entropy of the time-frequency plane is acquired, which can be used to quantitatively express the uniformity of the distribution of the feeder current signal's energy in the plane. Differences in uniformity can indicate differences among operating states of DC traction network, which makes it possible to distinguish the oscillation current and short-circuit fault current in DC traction network by means of multi-scale time-frequency entropy. On the basis of simulation analysis and field data calculation, availability of the suggested approach is certified.关键词
直流牵引网/振荡电流/短路故障电流/改进局部均值分解/多尺度时频熵Key words
DC traction network/oscillation current/short-circuit fault current/improved local mean decomposition/multi-scale time-frequency entropy引用本文复制引用
杨洪耕,冷月,王智琦..用ILMD多尺度时频熵识别直流牵引网振荡电流与故障电流[J].高电压技术,2018,44(8):2457-2463,7.基金项目
国家自然科学基金(51477105).Project supported by National Natural Science Foundation of China(51477105). （51477105）
