JOURNAL BROWSE
Search
Advanced SearchSearch Tips
Implementation of Real-time Data Stream Processing for Predictive Maintenance of Offshore Plants
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
  • Journal title : Journal of KIISE
  • Volume 42, Issue 7,  2015, pp.840-845
  • Publisher : Korean Institute of Information Scientists and Engineers
  • DOI : 10.5626/JOK.2015.42.7.840
 Title & Authors
Implementation of Real-time Data Stream Processing for Predictive Maintenance of Offshore Plants
Kim, Sung-Soo; Won, Jongho;
 
 Abstract
In recent years, Big Data has been a topic of great interest for the production and operation work of offshore plants as well as for enterprise resource planning. The ability to predict future equipment performance based on historical results can be useful to shuttling assets to more productive areas. Specifically, a centrifugal compressor is one of the major piece of equipment in offshore plants. This machinery is very dangerous because it can explode due to failure, so it is necessary to monitor its performance in real time. In this paper, we present stream data processing architecture that can be used to compute the performance of the centrifugal compressor. Our system consists of two major components: a virtual tag stream generator and a real-time data stream manager. In order to provide scalability for our system, we exploit a parallel programming approach to use multi-core CPUs to process the massive amount of stream data. In addition, we provide experimental evidence that demonstrates improvements in the stream data processing for the centrifugal compressor.
 Keywords
stream computing;predictive maintenance;Big Data;complex event processing;
 Language
Korean
 Cited by
 References
1.
Haridoss Padmanabhan, "Condition Based Maintenance of Rotating Equipments on OSI PI Platform," Refineries/Petrochem Plants, 2010.

2.
Jill Geblowitz, "The big deal about big data in upstream oil and gas," IDC Energy Insights, 2012.

3.
L.S. Edison, J.D. Brantley, "The value of smarter oil and gas fields: Unlocking the full value of your assets," IBM Center for Applied Insights, White Paper, May 2011.

4.
Bently Performance SE, "Helping protect and manage all machinery," Fact sheet, 2013.

5.
ASME PTC 10-1997, "Performance Test Code on Compressors and Exhausters," 1997.

6.
"Business Overview of PRODML," Engergistics and PRODML SIG, 2012.

7.
http://esper.codehaus.org/about/esper/esper.html

8.
http://sungsoo.github.io/2014/02/03/using-bytebufferin-java.html