The role of wireless sensor networks (WSNs) in industrial oil and gas condition monitoring

Akhondi, Mohammad Reza; Talevski, Alex; Carlsen, S.; Petersen, S.

doi:10.1109/DEST.2010.5610584

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Access Status

Open access

Authors

Akhondi, Mohammad Reza

Talevski, Alex

Carlsen, S.

Petersen, S.

Date

2010

Type

Conference Paper

Metadata

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Citation

Akhondi, Mohammad Reza and Talevski, Alex and Carlsen, Simon and Petersen, Stig. 2010. The role of wireless sensor networks (WSNs) in industrial oil and gas condition monitoring, in Ismail, L. and Chang, E. and Karduck, A.P. (ed), IEEE international conference on digital ecosystems and technologies (DEST 2010), Apr 12 2010, pp. 618-623. Dubai, United Arab Emirates: IEEE.

Source Title

Proceedings of the IEEE international conference on digital ecosystems and technologies (DEST 2010)

Source Conference

IEEE international conference on digital ecosystems and technologies (DEST 2010)

DOI

10.1109/DEST.2010.5610584

ISBN

9781424455515

School

Digital Ecosystems and Business Intelligence Institute (DEBII)

Remarks

Copyright © 2010 IEEE This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

URI

http://hdl.handle.net/20.500.11937/30613

Collection

Curtin Research Publications

Abstract

Wireless sensor networks have a vast amount of applications including environmental monitoring, military, ecology, agriculture, inventory control, robotics and health care. This paper focuses on the area of monitoring and protection of oil and gas operations using wireless sensor networks that are optimized to decrease installation, and maintenance cost, energy requirements, increase reliability and improve communication efficiency. In addition, simulation experiments using the proposed model are presented. Such models could provide new tools for research in predictive maintenance and condition-based monitoring of factory machinery in general and for “open architecture machining systems” in particular. Wireless sensing no longer needs to be relegated to locations where access is difficult or where cabling is not practical. Wireless condition monitoring systems can be cost effectively implemented in extensive applications that were historically handled by running routes with data collectors.The result would be a lower cost program with more frequent data collection, increased safety, and lower spare parts inventories. Facilities would be able to run leaner because they will have more confidence in their ability to avoid downtime.