用于教育和培训的物联网机器健康监测模型

Ishwar Singh, S. Hodgins, Anoop Gadhrri, Reiner Schmidt
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引用次数: 1

摘要

物联网、IIoT 和工业 4.0 技术正在引领制造、医疗保健、交通、能源、零售、城市、供应链、农业、楼宇和其他行业的数字化转型。旋转机器的机器健康监测和预测性维护是制造业和能源行业中的一个创新 IIoT 用例。本章将介绍如何利用先进的传感器技术实施机器健康监测,以此作为旋转设备预测性维护的基础。本章还将介绍如何从边缘设备收集传感器数据,并在微控制器/边缘节点中进行预处理,然后发送到云端或本地服务器,以实现高级数据智能。此外,本章还介绍了三种创新型教育和培训模式的设计和运行,以支持工业部门加速采用这些技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
IIoT Machine Health Monitoring Models for Education and Training
IoT, IIoT and Industry 4.0 technologies are leading the way for digital transformation in manufacturing, healthcare, transportation, energy, retail, cities, supply chain, agriculture, buildings, and other sectors. Machine health monitoring and predictive maintenance of rotating machines is an innovative IIoT use case in the manufacturing and energy sectors. This chapter covers how machine health monitoring can be implemented using advanced sensor technology as a basis for predictive maintenance in rotating devices. It also covers how sensor data can be collected from the devices at the edge, preprocessed in a microcontroller/edge node, and sent to the cloud or local server for advanced data intelligence. In addition, this chapter describes the design and operation of three innovative models for education and training supporting the accelerated adoption of these technologies in industry sectors.
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