A multi–modal unsupervised fault detection system based on power signals and thermal imaging via deep AutoEncoder neural network

In this paper a multi-modal unsupervised Deep Learning based algorithm for fault detection is proposed. Such method is applied to real data from a testing procedure implemented on an industrial production line. Both thermal images and current and power measurements coming from industrial refrigerato...

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Vydané v:	Engineering applications of artificial intelligence Ročník 110; s. 104729
Hlavní autori:	Cordoni, Francesco, Bacchiega, Gianluca, Bondani, Giulio, Radu, Robert, Muradore, Riccardo
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Ltd 01.04.2022
Predmet:	Auto-encoder neural network Deep convolutional neural network Deep Learning Fault detection and isolation Neural networks Predictive maintenance Thermal camera Unsupervised learning Neural networks Fault detection and isolation Auto-encoder neural network Deep convolutional neural network Deep Learning Unsupervised learning Thermal camera Predictive maintenance
ISSN:	0952-1976, 1873-6769
On-line prístup:	Získať plný text
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