In the context of industry 4.0, it is strategic to support factories with innovative maintenance approaches, so to avoid faults and decrease the risks of a production stop. The first step of the digitization of factories has been the collection of large amounts of data monitoring the health status of the plant. However, such data is of little use unless it is clearly correlated with information about faults occurred on the line: some faults may be sporadic, or happen only in extremely critical conditions, and thus no data may be available related to their occurrence. Artificially generating such data would force to actually damage the plant, that is of course not a viable solution. The goal of this work is to generate faulty temporal series, that reproduce the behavior of a component on the occurrence of specific faults. The innovative approach models the component of interest in Verilog-AMS (VAMS) and systematically injects the faults of interest, by keeping a direct link with the real possible cause of such faulty behavior on the plant. To prove the effectiveness of the proposed solution, the approach is applied to a direct current motor (DC motor), an electromechanical system that converts electrical energy into mechanical energy.
Functionality and Fault Modeling of a DC Motor with Verilog-AMS / Dall'Ora, Nicola; Vinco, Sara; Fummi, Franco. - (2020), pp. 35-40. (Intervento presentato al convegno IEEE International Conference on Industrial Informatics (INDIN) tenutosi a Warwick, United Kingdom nel 20-23 July 2020) [10.1109/INDIN45582.2020.9442191].
Functionality and Fault Modeling of a DC Motor with Verilog-AMS
Sara Vinco;Franco Fummi
2020
Abstract
In the context of industry 4.0, it is strategic to support factories with innovative maintenance approaches, so to avoid faults and decrease the risks of a production stop. The first step of the digitization of factories has been the collection of large amounts of data monitoring the health status of the plant. However, such data is of little use unless it is clearly correlated with information about faults occurred on the line: some faults may be sporadic, or happen only in extremely critical conditions, and thus no data may be available related to their occurrence. Artificially generating such data would force to actually damage the plant, that is of course not a viable solution. The goal of this work is to generate faulty temporal series, that reproduce the behavior of a component on the occurrence of specific faults. The innovative approach models the component of interest in Verilog-AMS (VAMS) and systematically injects the faults of interest, by keeping a direct link with the real possible cause of such faulty behavior on the plant. To prove the effectiveness of the proposed solution, the approach is applied to a direct current motor (DC motor), an electromechanical system that converts electrical energy into mechanical energy.File | Dimensione | Formato | |
---|---|---|---|
09442191.pdf
non disponibili
Tipologia:
2a Post-print versione editoriale / Version of Record
Licenza:
Non Pubblico - Accesso privato/ristretto
Dimensione
718.32 kB
Formato
Adobe PDF
|
718.32 kB | Adobe PDF | Visualizza/Apri Richiedi una copia |
Pubblicazioni consigliate
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
https://hdl.handle.net/11583/2907616