Unsupervised Monitoring System for Predictive Maintenance of High Voltage Apparatus

Unsupervised Monitoring System for Predictive Maintenance of High Voltage Apparatus

The online monitoring of a high voltage apparatus is a crucial aspect for a predictive maintenance program. Partial discharges (PDs) phenomena affect the insulation system of an electrical machine and—in the long term—can lead to a breakdown, with a consequent, significant econom...

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Main Authors: Christian Gianoglio, Edoardo Ragusa, Andrea Bruzzone, Paolo Gastaldo, Rodolfo Zunino, Francesco Guastavino
Format: Article
Language:English
Published: MDPI AG 2020-03-01
Series:Energies
Subjects:
predictive maintenance
embedded systems
partial discharges
Online Access:https://www.mdpi.com/1996-1073/13/5/1109
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spelling doaj-4ea26996a9d74f3fbd060fe544f9184c2020-11-25T03:00:58ZengMDPI AGEnergies1996-10732020-03-01135110910.3390/en13051109en13051109Unsupervised Monitoring System for Predictive Maintenance of High Voltage ApparatusChristian Gianoglio0Edoardo Ragusa1Andrea Bruzzone2Paolo Gastaldo3Rodolfo Zunino4Francesco Guastavino5Electrical, Electronics and Telecommunication Engineering and Naval Architecture Department (DITEN), University of Genoa, 16145 Genova, ItalyElectrical, Electronics and Telecommunication Engineering and Naval Architecture Department (DITEN), University of Genoa, 16145 Genova, ItalyElectrical, Electronics and Telecommunication Engineering and Naval Architecture Department (DITEN), University of Genoa, 16145 Genova, ItalyElectrical, Electronics and Telecommunication Engineering and Naval Architecture Department (DITEN), University of Genoa, 16145 Genova, ItalyElectrical, Electronics and Telecommunication Engineering and Naval Architecture Department (DITEN), University of Genoa, 16145 Genova, ItalyElectrical, Electronics and Telecommunication Engineering and Naval Architecture Department (DITEN), University of Genoa, 16145 Genova, ItalyThe online monitoring of a high voltage apparatus is a crucial aspect for a predictive maintenance program. Partial discharges (PDs) phenomena affect the insulation system of an electrical machine and—in the long term—can lead to a breakdown, with a consequent, significant economic loss; wind turbines provide an excellent example. Embedded solutions are therefore required to monitor the insulation status. The paper presents an online system that adopts unsupervised methodologies for assessing the condition of the monitored machine in real time. The monitoring process does not rely on any prior knowledge about the apparatus; nonetheless, the method can identify the relevant drifts in the machine status. In addition, the system is specifically designed to run on low-cost embedded devices.https://www.mdpi.com/1996-1073/13/5/1109predictive maintenanceembedded systemspartial discharges
collection DOAJ
language English
format Article
sources DOAJ
author Christian Gianoglio
Edoardo Ragusa
Andrea Bruzzone
Paolo Gastaldo
Rodolfo Zunino
Francesco Guastavino
spellingShingle Christian Gianoglio
Edoardo Ragusa
Andrea Bruzzone
Paolo Gastaldo
Rodolfo Zunino
Francesco Guastavino
Unsupervised Monitoring System for Predictive Maintenance of High Voltage Apparatus
Energies
predictive maintenance
embedded systems
partial discharges
author_facet Christian Gianoglio
Edoardo Ragusa
Andrea Bruzzone
Paolo Gastaldo
Rodolfo Zunino
Francesco Guastavino
author_sort Christian Gianoglio
title Unsupervised Monitoring System for Predictive Maintenance of High Voltage Apparatus
title_short Unsupervised Monitoring System for Predictive Maintenance of High Voltage Apparatus
title_full Unsupervised Monitoring System for Predictive Maintenance of High Voltage Apparatus
title_fullStr Unsupervised Monitoring System for Predictive Maintenance of High Voltage Apparatus
title_full_unstemmed Unsupervised Monitoring System for Predictive Maintenance of High Voltage Apparatus
title_sort unsupervised monitoring system for predictive maintenance of high voltage apparatus
publisher MDPI AG
series Energies
issn 1996-1073
publishDate 2020-03-01
description The online monitoring of a high voltage apparatus is a crucial aspect for a predictive maintenance program. Partial discharges (PDs) phenomena affect the insulation system of an electrical machine and—in the long term—can lead to a breakdown, with a consequent, significant economic loss; wind turbines provide an excellent example. Embedded solutions are therefore required to monitor the insulation status. The paper presents an online system that adopts unsupervised methodologies for assessing the condition of the monitored machine in real time. The monitoring process does not rely on any prior knowledge about the apparatus; nonetheless, the method can identify the relevant drifts in the machine status. In addition, the system is specifically designed to run on low-cost embedded devices.
topic predictive maintenance
embedded systems
partial discharges
url https://www.mdpi.com/1996-1073/13/5/1109
work_keys_str_mv AT christiangianoglio unsupervisedmonitoringsystemforpredictivemaintenanceofhighvoltageapparatus
AT edoardoragusa unsupervisedmonitoringsystemforpredictivemaintenanceofhighvoltageapparatus
AT andreabruzzone unsupervisedmonitoringsystemforpredictivemaintenanceofhighvoltageapparatus
AT paologastaldo unsupervisedmonitoringsystemforpredictivemaintenanceofhighvoltageapparatus
AT rodolfozunino unsupervisedmonitoringsystemforpredictivemaintenanceofhighvoltageapparatus
AT francescoguastavino unsupervisedmonitoringsystemforpredictivemaintenanceofhighvoltageapparatus
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