This work studies the impact of Wireless Sensor Networks (WSNs) for oil spill detection in subsea OilGas applications. The case study is the Goliat FPSO where one WSN with passive acoustic sensors is assumed to be installed on each subsea template to monitor the manifold. Sensors take local binary decisions regarding the presence/absence of a spill by performing an energy test. A Fusion Center (FC) collects such local decisions and provides a more reliable global binary decision. The Counting Rule (CR) and a modified Chair-Varshney Rule (MCVR) are compared. An objective function derived from the Receiver Operating Characteristic (ROC) is used for threshold design. The considered methodology requires the knowledge of the involved subsea production system, in particular of its hotspots whose failure could cause an oil spill.

Data Fusion for Subsea Oil Spill Detection through Wireless Sensor Networks / Tabella G.; Paltrinieri N.; Cozzani V.; Rossi P.S.. - ELETTRONICO. - 2020-:(2020), pp. 9278741.1-9278741.4. (Intervento presentato al convegno 2020 IEEE Sensors, SENSORS 2020 tenutosi a nld nel 2020) [10.1109/SENSORS47125.2020.9278741].

Data Fusion for Subsea Oil Spill Detection through Wireless Sensor Networks

Cozzani V.;
2020

Abstract

This work studies the impact of Wireless Sensor Networks (WSNs) for oil spill detection in subsea OilGas applications. The case study is the Goliat FPSO where one WSN with passive acoustic sensors is assumed to be installed on each subsea template to monitor the manifold. Sensors take local binary decisions regarding the presence/absence of a spill by performing an energy test. A Fusion Center (FC) collects such local decisions and provides a more reliable global binary decision. The Counting Rule (CR) and a modified Chair-Varshney Rule (MCVR) are compared. An objective function derived from the Receiver Operating Characteristic (ROC) is used for threshold design. The considered methodology requires the knowledge of the involved subsea production system, in particular of its hotspots whose failure could cause an oil spill.
2020
Proceedings of IEEE Sensors
1
4
Data Fusion for Subsea Oil Spill Detection through Wireless Sensor Networks / Tabella G.; Paltrinieri N.; Cozzani V.; Rossi P.S.. - ELETTRONICO. - 2020-:(2020), pp. 9278741.1-9278741.4. (Intervento presentato al convegno 2020 IEEE Sensors, SENSORS 2020 tenutosi a nld nel 2020) [10.1109/SENSORS47125.2020.9278741].
Tabella G.; Paltrinieri N.; Cozzani V.; Rossi P.S.
File in questo prodotto:
Eventuali allegati, non sono esposti

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/795196
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 5
  • ???jsp.display-item.citation.isi??? 1
social impact