摘要
研究一种适应当前电力大数据环境的设备状态检修管理信息系统。在层次化电力大数据系统支持下,开发该系统仅在数据的策略层(Strategy Layer)开发2个神经网络模块和1个模糊策略矩阵;在应用层开发1套可视化脚本,即可完成系统的开发工作。在该开发策略下,以较小的开发量、较小的硬件新增量为前提,实现了完全满足开发需求的开发任务;该系统的不同预警状态均表现出较强的预警判断敏感性。
This paper studies an equipment condition based maintenance management information system suitable for the current power big data environment.With the support of hierarchical power big data system,the development of the system only needs to develop two neural network modules and one fuzzy strategy matrix in the strategy layer of data,and develop a set of visual script in the application layer to complete the system development.Under this development strategy,the development task that fully meets the development requirements is realized under the premise of small development amount and small hardware new increment.The different early warning states of the system show strong sensitivity of early warning judgment.
作者
王立峰
马超
牛永光
苏彪
刘祥振
辛思远
WANG Lifeng;MA Chao;NIU Yongguang;SU Biao;LIU Xiangzhen;XIN Siyuan(Shandong Luruan Digital Technology Co.,Ltd.,Jinan 250000,China)
出处
《粘接》
CAS
2022年第10期176-179,共4页
Adhesion
关键词
电力大数据
层次模型
状态检修
设备监测
开发策略
power big data
hierarchical model
condition based maintenance
equipment monitoring
development strategy
作者简介
王立峰(1975-)男,本科,主要从事电力设备可靠性、预警、诊断研究。
