基于ECIM模型的电力物联设备自描述属性关联融合系统设计  

Design of self-description attribute association fusion system for power IoT equipment based on ECIM model

作　　者：李颖杰 黄兵 LI Yingjie;HUANG Bing(Shenzhen Power Supply Co.,Ltd.,Shenzhen 518000,China;China Southern Power Grid Shenzhen Digital Grid Research Institute Co.,Ltd.,Shenzhen 518000,China)

机构地区：[1]深圳供电局有限公司,广东深圳518000 [2]南方电网深圳数字电网研究院有限公司,广东深圳518000

出　　处：《电子设计工程》2023年第2期59-62,67,共5页Electronic Design Engineering

摘　　要：为了实现电力物联设备自描述属性关联融合检测以及设备信息化管理,设计了基于ECIM模型的电力物联设备自描述属性关联融合系统。构建电力物联设备自描述属性关联特征分析模型,挖掘电力物联设备自描述属性大数据,通过特征空间重组和信息融合方法实现对电力物联设备自描述属性分类检测,采用ECIM模型调度电力物联设备自描述属性关联;通过非连续换相指标分析方法,实现对电力物联设备自描述特征融合和模糊度信息识别。采用模糊属性聚类和样本分段检测方法,实现对电力物联设备自描述属性关联融合和优化调度。实验结果表明,采用所设计系统进行电力物联设备自描述属性关联融合的检测性能较好,信息识别度较高,有助于提高电力物联设备的信息化管理能力。In order to realize the self description attribute association fusion detection and equipment information management of power IoT equipment,a self description attribute association fusion system of power IoT equipment based on ECIM model is designed.Build the self describing attribute association feature analysis model of power IoT equipment,mine the big data of self describing attribute of power IoT equipment,classify and detect the self describing attribute of power IoT equipment through feature space reorganization and information fusion,and dispatch the self describing attribute association of power IoT equipment by ECIM model;Through the discontinuous commutation index analysis method,the self description feature fusion and fuzzy information recognition of power IoT equipment are realized.Fuzzy attribute clustering and sample segmentation detection methods are used to realize self describing attribute association fusion and optimal scheduling of power IoT equipment.The experimental results show that the designed system has better detection performance and higher information recognition,which is helpful to improve the information management ability of power IoT equipment.

关 键 词：ECIM模型 电力物联设备 自描述属性 关联融合 

分 类 号：TN-9[电子电信]