IIoT Solution for predictive monitoring based on vibration data from motors using Microsoft Azure machine learning studio and Power BI

Ravi Helon M. S. Ferreira, Lucas O. de Figueiredo, Rafael B. C. Lima, Luiz Antonio Pereira Silva, P. R. Barros
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Abstract

This article presents the design and development of a practical predictive monitoring system. There are three main sections to it: vibration data acquisition, data analytics, and presentation of a report. An STM32F446RE microcontroller does the data acquisition. The Data analytics step the training of different machine learning models and determining which one gives the best results, using Azure Machine Learning. Microsoft PowerBi generates a report that uses all the available information, before and after diagnostics. Lastly, a cloud-based Azure Storage Account stores the information at every step.
IIoT解决方案,基于来自电机的振动数据,使用Microsoft Azure机器学习工作室和Power BI进行预测监测
本文介绍了一种实用的预测监测系统的设计与开发。它有三个主要部分:振动数据采集、数据分析和报告呈现。STM32F446RE微控制器负责数据采集。数据分析步骤训练不同的机器学习模型,并确定哪一个提供最好的结果,使用Azure机器学习。Microsoft PowerBi生成一个报告,其中使用诊断前后的所有可用信息。最后,基于云的Azure存储帐户存储每一步的信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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