Pubblicazioni

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:

29 novembre 2022

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 CONGRESS , Atti di "INTERNATIONAL FEDERATION OF AUTOMATIC CONTROL WORLD CONGRESS" , Berlin, Germany , July 12-17, 2020 , 2020 , pp. 1-6

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