Suzhou Electric Appliance Research Institute
期刊号: CN32-1800/TM| ISSN1007-3175

Article retrieval

文章检索

首页 >> 文章检索 >> 往年索引

基于多信息融合的架空输电线路覆冰舞动预测方法

来源:电工电气发布时间:2022-10-25 12:25 浏览次数:243

基于多信息融合的架空输电线路覆冰舞动预测方法

徐伟进1,徐炜彬1,王贺冉2,杨欢2
(1 国网吉林省电力有限公司长春供电公司,吉林 长春 130000;
2 长春工业大学 电气与电子工程学院,吉林 长春 130012)
 
    摘 要:针对寒冷地区输电线路覆冰程度难以预测的问题,提出了一种基于多信息融合的架空输电线路覆冰舞动预测方法。使用 ANSYS Workbench 软件对输电铁塔的机械结构模型进行应力分析,计算输电线路铁塔发生覆冰舞动时的特征点位移大小与倾角变化,选择合适位置放置倾角传感器与振动传感器;当线路运行时,通过塔身传感器信息,收集覆冰时的实时气象数据,构建非线性四分类支持向量机(SVM)对覆冰情况进行预测分类。验证结果显示,该方法可以实现线路覆冰舞动现象的提前预警,预测准确率较高,便于推广。
    关键词: 输电线路;覆冰预测;ANSYS Workbench 软件;应力分析;支持向量机
    中图分类号:TM726.3     文献标识码:A     文章编号:1007-3175(2022)10-0026-04
 
Prediction Method of Icing Galloping of Overhead Transmission
Line Based on Multi-Information Fusion
 
XU Wei-jin1, XU Wei-bin1, WANG He-ran2, YANG Huan2
(1 Changchun Power Supply Company, State Grid Jilin Electric Power Co., Ltd, Changchun 130000, China;
2 School of Electrical and Electronic Engineering, Changchun University of Technology, Changchun 130012, China)
 
    Abstract: The degree of icing of transmission lines in cold regions is difficult to predict. This paper proposed a method for predicting the icing and galloping of overhead transmission lines based on multi-information fusion. This study employed the ANSYS Workbench software to do the stress analysis of the mechanical structure model of the transmission tower. It calculated the displacement of the characteristic point and the change of the inclination angle when the transmission line tower has the phenomena of ice galloping and selected the appropriate position to place the inclination sensor and the vibration sensor.This study collected real-time meteorological data during icing while the line was running. In addition, it constructed a nonlinear four-class SVM to predict and classify the icing situation. The verification results show that this method could warn the icing and galloping of overhead transmission lines in advance.This method has higher accuracy of prediction,and it could be popularized in the industry.
    Key words: transmission line; icing prediction; ANSYS Workbench software; stress analysis; support vector machine
 
参考文献
[1] 金佛荣. 基于物联网的高压铁塔摆动预警装置的设计[J]. 科技风,2019(20):24.
[2] 陈露璐,李陶,刘艳,刘经南. 特高压输电铁塔聚束模式 SAR 干涉特性研究与覆冰试验[J] . 测绘通报,2019(12):30-34.
[3] 张元军,李清华. 电力铁塔运行状态智能在线监测的研究及应用[J]. 科技视界,2016(22):9-10.
[4] 牛唯,王斌,马晓红,李昊,毛先胤,李锐海. 均匀覆冰下的直线塔架空地线覆冰厚度计算模型误差分析[J]. 广东电力,2021,34(10):76-82.
[5] 左丽. 基于物联网的输电铁塔振动分析系统[D] .保定:华北电力大学,2013.
[6] 黄新波,廖明进,徐冠华,朱永灿,赵隆. 采用光纤光栅传感器的输电线路铁塔应力监测方法[J] .电力自动化设备,2016,36(4):68-72.
[7] 廖明进. 输电线路铁塔应力分析及在线监测技术研究[D]. 西安:西安工程大学,2016.
[8] 崔莉,陆文伟,葛乐,徐晓轶,杨志超. 基于有限元分析的输电铁塔实时应力计算系统[J] . 实验室研究与探索,2016,35(5):123-126.
[9] 电力规划设计总院. 架空输电线路杆塔结构设计技术规定:DL/T 5154—2012[S] . 北京:中国计划出版社,2012:13-21.
[10] 郭开春,王波. 考虑灰色关联权重的 PSO-LSSVM 输电线路覆冰厚度预测模型[J] . 电工材料,2022(1):15-19.
[11] 韩顺杰,齐冀樊,姜玉莲,尤文. 基于主成分分析与遗传算法-支持向量机的喷溅预测方法[J] . 钢铁研究学报,2016,28(12):21-26.
[12] GEETHA K.Evolutionary Multivariate Kernal Svm Prediction Method for Classification[J].International Journal of Innovative Technology and Exploring Engineering,2020,9(8):28-29.
[13] YIN Feifei, GONG Yu.DBSCAN and SVM for Fault Diagnosis of Wind Turbine Based on SCADA Data[J].International Core Journal of Engineering,2020,6(6):12-15.
[14] 朱永超,朱才朝,宋朝省,王屹立,杨妍妮.PCA-PSO/GS-SVM 组合方法在风电齿轮箱故障预测中的应用研究[J]. 太阳能学报,2021,42(3):35-42.
[15] AFIFI Shereen Moataz, GHOLAMHOSSEINI Hamid,SINHA Roopak.FPGA Implementations of SVM Classifiers: A Review[J].SN Computer Science,2020,1(3):23-28.