| 李 斌,娄 璟,杜典松.基于 SOA-SVM 的弓网电弧识别方法[J].电子测量与仪器学报,2022,36(10):83-91 |
| 基于 SOA-SVM 的弓网电弧识别方法 |
| Pantograph arc recognition method based on SOA-SVM |
| |
| DOI： |
| 中文关键词: 弓网电弧 故障识别 特征选择 海鸥优化算法 支持向量机 |
| 英文关键词:pantograph arc fault identification feature selection seagull optimization algorithm ( SOA) support vector machine
(SVM) |
| 基金项目:国家自然科学基金（52077158）项目资助 |
|
|
|
|
| 摘要点击次数: 1228 |
| 全文下载次数: 1188 |
| 中文摘要: |
| 受电弓-接触网作为牵引供电系统的重要组成部分关系着高速列车的安全与稳定,及早的对弓网电弧进行识别对于保
障列车稳定运行具有十分重要的意义。 通过计算更符合列运实际的“Z”字摩擦速率并对列车的运行时速、接触压力及接触电
流依次进行单变量调整,模拟了 4 种不同工况的弓网受流实验。 基于实验数据,从特征供给和参数优化两方面出发:首先,利用
D-score 评估准则对电流特征进行对比,筛选出电弧识别特征及其显著区间;其次,设计样本定容环节考察特征信息的完备性;
最后,利用海鸥算法( seagull optimization algorithm,SOA)优化支持向量机( support vector machine,SVM)对弓网电弧建模识别。
经测试结果与对比分析得出,SOA-SVM 能够快速、有效的对弓网电弧建模识别,平均识别水平达 98. 5%、总体识别水平在 97%
以上。 |
| 英文摘要: |
| As the important part of traction power supply system, pantograph and catenary are related to the safety and stability of highspeed train. It is of great significance to identify pantograph arc as soon as possible. By calculating the " Z" friction rate which is more
in line with the actual train operation, the running speed, contact pressure and contact current during train operation are adjusted in
single variable to simulate the pantograph arc experiment under four different working conditions. Based on the experimental data, the
features of pantograph catenary current are compared and analyzed by D-score at first, and the arc identification features and their
significant identification intervals are selected. At the same time, a method for finding the suitable number of samples containing
sufficient feature information is designed. Finally, seagull optimization algorithm is used to optimize support vector machine to model and
identify pantograph arc. The test results and comparative analysis show that SOA-SVM can quickly and effectively model and identify
pantograph catenary arc with an average recognition level of 98. 5% and an overall recognition level of more than 97%. |
| 查看全文 查看/发表评论 下载PDF阅读器 |
|
|
|
