Transient signal identification of HVDC transmission lines based on wavelet entropy and SVM
Transient signal identification of HVDC transmission lines based on wavelet entropy and SVM
复制标题
基于小波熵和SVM的高压直流输电线路暂态信号识别
DOI：
10.1049/joe.2018.8555
复制
发表时间：
2019-03-01
影响因子：
0.7
通讯作者：
Liu, Yinglin
中科院分区：
文献类型：
--
作者：
Luo, Guomin;Yao, Changyuan;Liu, Yinglin
High-voltage DC (HVDC) transmission plays an important role in power transmission projects due to its advantages of large transmission power and good control performance. As the main protection of the DC transmission line, transient protection uses the high-frequency signal generated by fault transient to detect faults, having the characteristics of fast response and high accuracy. However, the HVDC transmission line has complex conditions along the route and is vulnerable to lightning strikes and other accidents, resulting in the occurrence of a variety of transients in the line, which increases the difficulty of fault identification. Being able to reveal signal time-frequency characteristic, wavelet entropy is an effective tool of signal recognition. This study proposes a method of transient signal identification based on the wavelet entropy and support vector machine (SVM). Firstly, the transient processes of three kinds of signals, including unipolar faults, lightning strike faults, and lightning disturbances, are briefly introduced. Then the time-frequency features of three kinds of transient signals under different scenes are analysed by wavelet entropy. Finally, the training set was used to train the SVM classification model with the signal wavelet entropy being taken as the eigenvector, and the test results validate the effectiveness of the proposed method.
