Pubblicazioni

A deep learning unsupervised approach for fault diagnosis of household appliances  (2020)

Autori:
Cordoni, Francesco Giuseppe; Bacchiega, Gianluca; Bondani, Giulio; Radu, Robert; Muradore, Riccardo
Titolo:
A deep learning unsupervised approach for fault diagnosis of household appliances
Anno:
2020
Tipologia prodotto:
Contributo in atti di convegno
Tipologia ANVUR:
Contributo in Atti di convegno
Lingua:
Inglese
Formato:
Elettronico
Titolo del Convegno:
INTERNATIONAL FEDERATION OF AUTOMATIC CONTROL WORLD CONGRESS
Luogo:
Berlin, Germany
Periodo:
July 12-17, 2020
Intervallo pagine:
1-6
Parole chiave:
Fault detection and isolation, Deep Learning, Neural networks, Unsupervised Learning, Autoencoder Neural Networks
Breve descrizione dei contenuti:
Fault detection and fault diagnosis are crucial subsystems to be integrated within the control architecture of modern industrial processes to ensure high quality standards. In this paper we present a two-stage unsupervised approach for fault detection and diagnosis in household appliances. In particular a suitable testing procedure has been implemented on a real industrial production line in order to extract the most meaningful features that allow to efficiently classify different types of fault by consecutively exploiting deep autoencoder neural network and k-means or hierarchical clustering techniques.
Id prodotto:
113841
Handle IRIS:
11562/1015036
ultima modifica:
18 maggio 2021
Citazione bibliografica:
Cordoni, Francesco Giuseppe; Bacchiega, Gianluca; Bondani, Giulio; Radu, Robert; Muradore, Riccardo, A deep learning unsupervised approach for fault diagnosis of household appliances  in INTERNATIONAL FEDERATION OF AUTOMATIC CONTROL WORLD CONGRESSAtti di "INTERNATIONAL FEDERATION OF AUTOMATIC CONTROL WORLD CONGRESS" , Berlin, Germany , July 12-17, 2020 , 2020pp. 1-6

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