|本期目录/Table of Contents|

[1]李波,李鹏,高莲,等.基于PCA-VMD-CNN的输电线路覆冰重量预测模型*[J].中国安全生产科学技术,2022,18(10):216-222.[doi:10.11731/j.issn.1673-193x.2022.10.032]
　LI Bo,LI Peng,GAO Lian,et al.Prediction model for weight of ice coating on transmission line based on PCA-VMD-CNN[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2022,18(10):216-222.[doi:10.11731/j.issn.1673-193x.2022.10.032]
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基于PCA-VMD-CNN的输电线路覆冰重量预测模型*
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《中国安全生产科学技术》[ISSN:1673-193X/CN:11-5335/TB]

卷:
18
期数:
2022年10期
页码:
216-222
栏目:
职业安全卫生管理与技术
出版日期:
2022-10-31

文章信息/Info

Title:
Prediction model for weight of ice coating on transmission line based on PCA-VMD-CNN
文章编号:
1673-193X(2022)-10-0216-07
作者:
李波; 李鹏; 高莲; 杨家全; 包慧琪
(1.云南大学 信息学院，云南 昆明 650500；
2.云南省高校物联网技术及应用重点实验室，云南 昆明 650500；
3.云南省电网有限责任公司，云南 昆明 650217；
4.云南大学 软件学院，云南 昆明 650500)
Author(s):
LI Bo;  LI Peng;  GAO Lian;  YANG Jiaquan;  BAO Huiqi
(1.School of Information,Yunnan University,Kunming Yunnan 650500,China;
2.Yunnan Key Laboratory of Internet of Things Technology and Application,Kunming Yunnan 650500,China;
3.Yunnan Power Grid Co.,Ltd.,Kunming Yunnan 650217,China;
4.School of Software,Yunnan University,Kunming Yunnan 650500,China)
关键词:
输电线路; 主成分分析; 变分模态分解; 卷积神经网络; 多步长预测
Keywords:
transmission line;  principal component analysis (PCA);  variational modal decomposition (VMD);  convolutional neural network (CNN);  multiple step size prediction
分类号:
X934
DOI:
10.11731/j.issn.1673-193x.2022.10.032
文献标志码:
A
摘要:
为防止覆冰灾害危及电路安全，提出1种输电线路覆冰重量预测模型。首先对多个气象因素进行主成分分析提取气象因素中的有效信息，再对覆冰历史数据进行变分模态分解，获得具有不同特性的本征模态分量；然后基于卷积神经网络，对具有不同时间尺度（周期性、波动性不同）的各个分量进行训练及预测，并将每个分量的预测结果相加。研究结果表明：通过对某覆冰区域的输电线路监测数据进行实验仿真，研究所提出的覆冰重量预测模型有更高精度。
Abstract:
In order to prevent the ice coating disaster from endangering the transmission line safety,a prediction model for the weight of ice coating on the transmission line was proposed.Firstly,the principal component analysis (PCA) of multiple meteorological factors was carried out to extract the effective information of meteorological factors,and the variational modal decomposition (VMD) was carried out on the historical data of ice coating to obtain the eigenmodal components with different characteristics.Then,based on the convolutional neural network (CNN),each component with different time scales (different periodicity and volatility) was trained and predicted,and the prediction results of each component were added.Through the experimental simulation on the monitoring data of transmission line in an ice coating area,the experimental results showed that the proposed prediction model for the weight of ice coating had higher accuracy.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期： 2022-01-05
* 基金项目： 国家自然科学基金项目（61763049）；中青年学术和技术带头后备人才项目（202005AC160115）
作者简介： 李波，硕士研究生，主要研究方向为物联网环境下输电线路覆冰灾害预警模型。
通信作者： 李鹏，博士，副教授，主要研究方向为电力系统可靠性分析与维护决策、电力信息物理融合系统。
更新日期/Last Update: 2022-11-13