电力企业无感识别智能工器具管理系统设计与实现

Design and Realization of Intelligent Tools and Instruments Management System for Non-inductive Recognition in Power Enterprises

基于无感识别技术、物联网技术和云计算平台,构建了面向电力企业的物联网系统架构,结合远程视频监控平台,设计了一款电力企业工器具智能管理系统。所设计的智能管理系统从软件和硬件方面整合了电力企业的各类工具器,在管理系统中加入了RFID(Radio Frequency Identification technology)、视频实时监控、大数据挖掘和无感识别模块,并与数据采集与监视控制系统(SCADA)进行了数据交换,以此实现数据整合。同时,本文利用大数据挖掘技术实现了工器具管理系统的全生命周期管理,对工器具的状态及使用进行了预测和管理,并在机器学习算法的帮助下,使大量的数据能够被较好地应用和管理。最终的系统测试结果显示,所设计的无感识别智能工器具管理系统不仅在添加了人工智能技术和无感识别技术之后能够保证较高的准确率,也能够在较大的用户并发量下保证良好的网络负载能力和系统综合性能。

Based on the non-inductive recognition technology,the Internet of Things technology and the cloud computing platform,an Internet of Things system architecture for electric power enterprises was constructed,combined with a remote video monitoring platform,an intelligent management system for tools and appliances for electric power enterprises was designed.The designed intelligent management system integrated various tools of electric power enterprises from the aspects of software and hardware,added RFID (Radio Frequency Identification),video real-time monitoring,big data mining and non-inductive recognition modules to the management system,and exchanged data with the data acquisition and monitoring control system to achieve data integration.At the same time,big data mining technology was used to realize the full life cycle management of the tool and equipment management system,and to predict and manage the status and use of tools and equipment,and with the help of machine learning algorithms,a large amount of data can be better applied and managed.The final system test results showed that the designed non-inductive recognition intelligent tool management system not only can ensure a higher accuracy rate after adding artificial intelligence technology and non-inductive recognition technology,but also ensure good network load capacity and comprehensive system performance under a large amount of concurrent users.