首页|基于CNN的海上风电交流送出线路继电保护状态监测技术研究

基于CNN的海上风电交流送出线路继电保护状态监测技术研究

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为了提高海上风电场的可靠性,深入探讨了基于卷积神经网络(CNN)的海上风电交流送出线路继电保护状态监测技术.该技术通过实时采集继电保护设备的多维度运行数据,构建多视图数据集,并设计了一种融合多视图特征的CNN模型,用于评估继电保护设备的健康状态.与传统单视图的方法相比,多视图CNN能更全面地挖掘设备运行状态的内在关联,提高状态评估的准确性.
Research on the State Monitoring Technology of Relay Protection for Offshore Wind Power AC Transmission Lines Based on CNN
In order to enhance the reliability of offshore wind farms,this paper deeply explores the state monitoring tech-nology of relay protection for offshore wind power AC transmission lines based on Convolutional Neural Networks(CNN).The technology collects multidimensional operational data of relay protection equipment in real time,constructs a multi-view dataset,and designs a CNN model that integrates multi-view features to assess the health status of relay protection equipment.Compared with traditional single-view methods,multi-view CNN can more comprehensively explore the intrin-sic correlations of equipment operation status,improving the accuracy of status assessment.

offshore vind powerconvolutional neural networksrelay protectionstate monitoring

王德星

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国电投南通新能源公司,江苏 南通 226400

海上风电 卷积神经网络 继电保护 状态监测

2024

电工技术
重庆西南信息有限公司(原科技部西南信息中心)

电工技术

影响因子:0.177
ISSN:1002-1388
年,卷(期):2024.(22)