基于热成像与先进算法的鸟类行为预测及预防策略研究

Research on bird behavior prediction and prevention strategies based on thermal imaging and advanced algorithms

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摘要文章聚焦于电力设施因鸟类活动引发的安全问题,采用热成像技术结合先进算法对鸟类行为进行多维度分析与预测,进而提出有效防鸟策略。通过构建热成像监测系统采集鸟类在电力设施周边的行为数据,运用深度学习算法对数据进行处理与特征提取,实现对鸟类栖息、筑巢、飞行路径等行为的精准预测。基于预测结果,综合考虑生态平衡与电力设施安全,制订了包括物理驱鸟、仿生驱鸟、智能预警的多层面防鸟策略,为保障电力系统稳定运行提供了创新性的解决方案。 This study focuses on the safety problems caused by bird activities in power facilities,using thermal imaging technology combined with advanced algorithm to conduct multi-dimensional analysis and prediction of bird behavior,and then puts forward effective bird-control strategies.By constructing a thermal imaging monitoring system to collect the behavior data of birds around the power facilities,the deep learning algorithm is used to process the data and extract the features,so as to realize the accurate prediction of birds’habitat,nesting andﬂight path behaviors.Based on the prediction results,considering the ecological balance and the safety of power facilities,multi-level anti-bird strategies including physical birdﬂooding,bionic birdﬂooding and intelligent warning are formulated,which provides innovative solutions for ensuring the stable operation of the power system.

作者孙志宇付云飞宋少帅陈海原陈长征 SUN Zhiyu;FU Yunfei;SONG Shaoshuai;CHEN Haiyuan;CHEN Changzheng

机构地区国网连云港供电公司

出处《电力系统装备》 2025年第2期63-65,共3页 Electric Power System Equipment

关键词热成像电力设施多维度防鸟策略 thermal imaging power facilities multi-dimensional bird prevention strategy

分类号 TM63 [电气工程—电力系统及自动化]