基于改进模糊聚类的PLC通信数据动态挖掘研究  

Dynamic Mining of PLC Communication Data Based on Improved Fuzzy Clustering

作　　者：陈亚茹 张娟娟 CHEN Yaru;ZHANG Juanjuan(School of Information and Electronic Engineering,Shangqiu Institute of Technology,Shangqiu 476000,China)

机构地区：[1]商丘工学院信息与电子工程学院,河南商丘476000

出　　处：《通信电源技术》2025年第2期19-21,共3页Telecom Power Technology

摘　　要：为提高数据挖掘的准确性,确保挖掘数据的代表性,引进改进模糊聚类算法,以可编程逻辑控制器(Programmable Logic Controller,PLC)通信数据为例,开展数据动态挖掘方法的设计。设计数据采样率,利用PLC通信接口实时采集数据,实现监测与集中处理。引入主成分分析技术,确定数据主成分方向,并基于改进模糊聚类设计通信数据空间映射与聚类。采用滑动窗口技术,实现数据的动态挖掘与特征提取。实验结果表明,设计的方法不仅可以在排除噪声干扰的条件下,实现对批量数据的动态挖掘,还能确保挖掘数据的价值性与代表性。In order to improve the accuracy of data mining and ensure the representativeness of mining data,an improved fuzzy clustering algorithm is introduced,and the design of data dynamic mining method is carried out by taking the communication data of Programmable Logic Controller(PLC)as an example.Design data sampling rate,collect data in real time by using PLC communication interface,and realize monitoring and centralized processing.Principal component analysis technology is introduced to determine the direction of data principal component,and spatial mapping and clustering of communication data are designed based on improved fuzzy clustering.Using sliding window technology,dynamic data mining and feature extraction are realized.The experimental results show that the designed method can not only realize dynamic mining of batch data under the condition of eliminating noise interference,but also ensure the value and representativeness of mining data.

关 键 词：改进模糊聚类 空间映射 挖掘方法 通信数据 可编程逻辑控制器(PLC) 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]