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A Smart Condition Monitoring System for HV Networks with Artificial Intelligence, Augmented Reality and Virtual Reality: Copyright Material IEEE, Paper No. PCIC-2018-37

机译:具有人工智能的HV网络智能条件监控系统,增强现实和虚拟现实:版权材料IEEE,纸质号PCIC-2018-37

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The authors present a conceptual design for a SMART asset monitoring solution for high voltage (HV) networks in the petrochemical industry. The paper discusses the potential for incorporating artificial intelligence (AI), augmented reality (AR) and virtual reality (VR) into an application of the Industrial Internet of Things (IIoT) for condition monitoring. The paper is a continuation of the work presented by the authors at the IEEE-PCIC 2017 conference in Calgary. The proposed asset management system analyses condition monitoring (CM) data and assesses the risk of failure data across complete HV networks. Knowledge of deteriorating asset condition provides the operator with an advanced, early warning of incipient mechanical and electrical faults. With knowledge of the severity and source of such faults, pinpointed preventative maintenance interventions can then made during planned maintenance outages. The complete HV network asset monitoring solution described includes permanent sensors and monitoring nodes deployed at strategic locations across the network. Processed data is passed via a local area network to local servers and then via secure data cloud transmission to a centralized monitoring server located at the CM headquarters. This central server operates a CM database that logs, displays, benchmarks and trends the condition data with comparison to a statistically-significant database of measurements. It is proposed in the IIoT solution proposed that this database will be downloadable to a smartphone/tablet for use by the field engineer. The monitoring technology will likely also incorporate a number of AI machine learning software modules for the de-noising of raw signals and the diagnosis of different types of defects within different types of HV plant items. The proposed SMART CM system includes an advanced graphical user interface (GUI) for viewing HV asset CM data along with operational and maintenance (O&M) data. The GUI will also be able to display both condition criticality and operational criticality (on a color-coded range of 0-100%) for individual HV plant items on a digitized mimic of the HV network's single-line diagram (SLD). This could also be combined with geometric positioning data of assets across the facility (including HV cable routes and lengths) to provide a fully digitized SMART network diagram for use in the IIoT asset management solution. Asset management data, combined with the application of the developing techniques of AI, AR and VR, will greatly help the user to visualize the plant items in 3-D, their position within the network, their condition and operational criticality along with all related asset management information together on one dashboard screen, downloaded onto smartphone/tablet. The paper concludes with a case study showing the development of a specification for a SMART IIoT asset condition monitoring solution suitable for a large petrochemical refining facility.
机译:作者对石化工业中的高压(HV)网络进行了智能资产监控解决方案的概念设计。本文讨论了将人工智能(AI),增强现实(AR)和虚拟现实(VR)纳入工业互联网(IIOT)的潜力,以进行病情监测。本文是在卡尔加里IEEE-PCIC 2017年会议上的作者提出的作品的延续。建议的资产管理系统分析条件监测(CM)数据,并评估完整的HV网络上的故障数据的风险。资产状况恶化的知识为操作员提供了先进,预警的初期的机械和电气故障。凭借这些故障的严重程度和来源,能够在计划的维护中断期间进行精确的预防性维护干预措施。描述的完整的HV网络资产监视解决方案包括在网络上的战略位置部署的永久传感器和监视节点。处理后的数据通过本地区域网络通过到本地服务器,然后通过安全数据云传输到位于CM总部的集中监控服务器。该中央服务器运行了CM数据库,该数据库将与统计上有重大的测量数据库进行比较,将其显示,显示,基准和趋势条件数据进行比较。它在IIOT解决方案中提出建议,该数据库将可下载到智能手机/平板电脑以供现场工程师使用。监控技术也可能包含许多AI机器学习软件模块,用于原始信号的去噪和不同类型的不同类型的HV植物物品中的不同类型缺陷的诊断。所提出的智能CM系统包括一个高级图形用户界面(GUI),用于查看HV资产CM数据以及操作和维护(O&M)数据。对于在HV网络的单线图(SLD)的数字化模拟中,为单个HV工厂项目,GUI还将能够显示条件临界和操作临界(在0-100%的颜色编码范围)上。这也可以与整个设施(包括HV电缆路线和长度)的资产的几何定位数据相结合,以提供用于IIT资产管理解决方案的全数字化智能网络图。资产管理数据与AI,AR和VR的开发技术相结合,将极大地帮助用户在3-D中可视化植物项目,它们在网络内的位置以及所有相关资产以及所有相关资产以及所有相关资产的情况管理信息在一起在一个仪表板屏幕上,下载到智能手机/平板电脑上。本文结束了案例研究,展示了适用于大型石化炼油设施的智能IIOT资产状况监测解决方案规范的发展。

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