文章基本信息

标题：Forecasting Appliances Failures: A Machine-Learning Approach to Predictive Maintenance
本地全文：下载
作者：Sofia Fernandes ; Mário Antunes ; Ana Rita Santiago 等
期刊名称：Information
电子版ISSN：2078-2489
出版年度：2020
卷号：11
期号：4
页码：208-220
DOI：10.3390/info11040208
出版社：MDPI Publishing
摘要：Heating appliances consume approximately 48 % of the energy spent on household appliances every year. Furthermore, a malfunctioning device can increase the cost even further. Thus, there is a need to create methods that can identify the equipment’s malfunctions and eventual failures before they occur. This is only possible with a combination of data acquisition, analysis and prediction/forecast. This paper presents an infrastructure that supports the previously mentioned capabilities and was deployed for failure detection in boilers, making possible to forecast faults and errors. We also present our initial predictive maintenance models based on the collected data.
关键词：big data applications; big data services; infrastructure; data processing; data analysis; predictive maintenance; machine learning big data applications ; big data services ; infrastructure ; data processing ; data analysis ; predictive maintenance ; machine learning