摘要
为提升风电厂设备状态监控效果、保障风电厂的稳定运行,研究了基于智能视频分析的风电厂设备状态监控系统。应用计算机图像视觉技术,获取相应设备状态监控视频图像。通过智能视频分析技术,预处理设备状态监控视频图像,提取设备状态特征量。结合灰色预测原理,构建风电厂设备状态监控模型。采用方差倒数法,确定构建模型的定正权重参数,以获取风电厂设备状态监控数值。制定设备状态监控结果判定规则,实现风电厂设备状态的精准监控。试验结果表明:该系统的设备状态监控误差平方和最小值为0.10。该系统的设备状态监控性能较佳,具有一定应用价值。
To improve the effect of equipment condition monitoring in wind power plant and ensure the stable operation of wind power plant,a condition monitoring system of wind power plant equipment based on intelligent video analysis is researched.Computer image vision technology is applied to obtain the corresponding equipment condition monitoring video images.Through intelligent video analysis technology,the equipment condition monitoring video images are preprocessed and the equipment condition feature quantity is extracted.Combined with the principle of gray prediction,a wind power plant equipment condition monitoring model is constructed.The inverse variance method is used to determine the fixed weight parameters of the model,and the equipment monitoring values of the wind power plant are obtained.The rules for determining the results of equipment condition monitoring are formulated to realize the accurate monitoring of the equipment condition of wind power plant.The test results show that the sum of squares of system’s equipment condition monitoring error is at least 0.10.The system’s equipment condition monitoring performance is better and has certain application value.
作者
郑卫剑
王欢
李涛
闫佳
ZHENG Weijian;WANG Huan;LI Tao;YAN Jia(Hebei Suntien New Energy Technology Co.,Ltd.,Zhangjiakou 075131,China)
出处
《自动化仪表》
2025年第7期71-75,共5页
Process Automation Instrumentation
基金
河北建投新能源有限公司科技基金资助项目(HBCT2021033013001h)。
关键词
风电厂
智能视频分析
运行状态
实时监控
风力发电模式
方差倒数法
Wind power plant
Intelligent video analysis
Operational status
Real-time monitoring
Wind power generation mode
Inverse variance method
作者简介
郑卫剑(1986-),男,学士,工程师,主要研究方向为大数据分析,数智化系统开发、建设与运维,E-mail:pengfeil0919@163.com。
