摘要
当前方法对运行电厂设备进行监测时存在监测运行时间长、聚类效果差和监测效果差的问题,为此提出物联网技术在电厂设备运行监测系统中的应用方法。对电力数据的状态进行评估聚类,生成电厂设备状态信息类别,基于隶属度最大原则生成电力状态信息集;在物联网技术的基础上计算节点间的欧氏距离,并采用横向近似的方法分析电力情况,最终经过对数据点的修正,确认出设备的异常数据点,实现电厂设备运行监测。实验结果表明,所提方法的监测运行时短、聚类效果好、监测效果好,以及监测结果平均误差小。
The current method has the problems of long monitoring operation time,poor clustering effect,and poor monitoring effect when monitoring the operating power plant equipment.For this reason,the application method of the Internet of Things technology in the power plant equipment operation monitoring system is proposed.The status of power data is evaluated and clustered to generate power plant equipment status information categories,generate power status information sets based on the principle of maximum membership;the Euclidean distance between nodes is calculated on the basis of the Internet of Things technology,and it is analyzed under the horizontal approximation method.For the power situation,the abnormal data points of the equipment are finally confirmed through the correction of the data points,and the operation of the power plant equipment is monitored.The experimental results show that the proposed method has short monitoring running time,good clustering effect,good monitoring effect,and small average error of monitoring results.
作者
王健宁
WANG Jianning(Power China Hebei Electric Power Engineering Co.,Ltd.,Shijiazhuang 050031,China)
出处
《机械与电子》
2022年第5期30-33,37,共5页
Machinery & Electronics
关键词
物联网
聚类
信息提取
欧氏距离
异常点监测
internet of things
clustering
information extraction
Euclidean distance
abnormal point monitoring