Forecast Model Update Based on a Real-Time Data Processing Lambda Architecture for Estimating Partial Discharges in Hydrogenerator

Forecast Model Update Based on a Real-Time Data Processing Lambda Architecture for Estimating Partial Discharges in Hydrogenerator

The prediction of partial discharges in hydrogenerators depends on data collected by sensors and prediction models based on artificial intelligence. However, forecasting models are trained with a set of historical data that is not automatically updated due to the high cost to collect sensors’ data a...

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Bibliographic Details
Main Authors: Fabio Henrique Pereira, Francisco Elânio Bezerra, Diego Oliva, Gilberto Francisco Martha de Souza, Ivan Eduardo Chabu, Josemir Coelho Santos, Shigueru Nagao Junior, Silvio Ikuyo Nabeta
Format: Article
Language:English
Published: MDPI AG 2020-12-01
Series:Sensors
Subjects:
autoregressive forecasting model
lambda architecture
partial discharges
power hydrogenerators
real-time data processing
Online Access:https://www.mdpi.com/1424-8220/20/24/7242

Internet

https://www.mdpi.com/1424-8220/20/24/7242

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