面向能源路由监测、网络安装和预测性维护的使能技术综述及应用

A. Massaro, A. Galiano, Giacomo Meuli, S. Massari
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引用次数: 22

摘要

能源路由器是研究替代能源的科学界最近感兴趣的话题。本文讨论了支持建筑安装和监测能效的技术,重点关注创新方面以及预测能源路由器设备风险和故障条件的方法。红外(IR)热成像和增强现实(AR)在这项工作中被认为是能源网络安装测试的潜在技术和预测维护工具,而热模拟、图像后处理和数据挖掘则改进了预测过程的分析。图像后处理已应用于热图像和WiFi AR。关于数据挖掘,我们应用了k-Means和人工神经网络–Ann基于测量数据获得输出。本文提出了一些支持建筑信息建模BIMin智能电网应用的工具、过程和方法。最后,我们通过完成场景概述,提供了一些与赋能技术相匹配的ISO标准。
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Overview and Application of Enabling Technologies Oriented on Energy Routing Monitoring, on Network Installation and on Predictive Maintenance
Energy routers are recent topics of interest for scientific community working on alternative energy. Enabling technologies supporting installation and monitoring energy efficiency in building are discussed in this paper, by focusing the attention on innovative aspects and on approaches to predict risks and failures conditions of energy router devices. Infrared (IR) Thermography and Augmented Reality (AR) are indicated in this work as potential technologies for the installation testing and tools for predictive maintenance of energy networks, while thermal simulation, image post-processing and data mining improve the analysis of the prediction process. Image postprocessing has been applied on thermal images and for WiFi AR. Concerning data mining we applied k-Means and Artificial Neural Network –ANNobtaining outputs based on measured data. The paper proposes some tools procedure and methods supporting the Building Information ModelingBIMin smart grid applications. Finally we provide some ISO standards matching with the enabling technologies by completing the overview of scenario .
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