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作 者:常开敏 CHANG Kaimin(Hefei Design and Research Institute of Coal Industry Co.,Ltd.,Hefei 230041,China)
机构地区:[1]煤炭工业合肥设计研究院有限责任公司,安徽合肥230041
出 处:《通信电源技术》2023年第12期69-71,共3页Telecom Power Technology
摘 要:针对当前10 kV变电站电气设备运行状态监测方法存在数据监测成功率与准确率较低的问题,提出基于机器视觉的10 kV变电站电气设备运行状态智能监测方法。应用工业相机对电气设备进行监测,并对原始监测图像进行标定与滤波处理。使用支持向量机(Support Vector Machine,SVM)对电力设备运行信息特征进行聚类,构建电气设备运行状态异常诊断模型,实现有效监测。实验结果表明:所提方法的监测成功率保持在97%以上,准确率在98%以上,监测效果较好。A machine vision based intelligent monitoring method for the operation status of electrical equipment in 10 kV substations is proposed to address the issues of low success and accuracy in data monitoring.Apply industrial cameras to monitor electrical equipment,and calibrate and filter the original monitoring images.Simultaneously use Support Vector Machine(SVM)to cluster the information features of power equipment operation,construct an abnormal diagnosis model for electrical equipment operation status,and achieve effective monitoring.The experimental results show that the monitoring success rate and accuracy of the intelligent monitoring method based on machine vision for the operating status of electrical equipment in 10 kV substations can be maintained at over 97%and 98%respectively,with good monitoring results.
关 键 词:机器视觉 电气设备 运行状态监测 10 kV变电站 图像处理
分 类 号:TM732[电气工程—电力系统及自动化]
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