Fault detection system in gas lift well based on artificial immune system
Araujo, M.; Aguilar, J.; Aponte, H.
Neural Networks, 2003. Proceedings of the International Joint Conference on
Volume 3, Issue , 20-24 July 2003 Page(s): 1673 - 1677 vol.3
Digital Object Identifier   10.1109/IJCNN.2003.1223658
Summary: In this paper we propose an Artificial Immune System for fault detection in gas lift oil well. Our novel approach inspired by the Immune System allows the application of a pattern recognition model to perform fault detection. A significant feature of our approach is its ability to dynamically learning the fluid patterns of the 'self' and predicting new patterns of the 'non-self'.

» View citation and abstract

Log in by entering your IEEE Web Account Username and Password.

IEEE Communications Society members: If you subscribe to the IEEE Electronic Periodicals Package or IEEE Electronic Periodicals Package Plus, you must access your subscription at www.comsoc.org.

Check with your librarian, information professional, or system manager to determine if you need to log in. Please complete the online Technical Support Form if you need assistance.

Select the Purchase History link to access the document. You will have 5 Days after purchase to access the Full Text PDF. Please complete the online Technical Support Form if you need assistance.

• Search and access Abstract records free of charge
• Register for table of contents alerts
• Purchase Full Text PDF documents

» Learn more about subscription options or how to become an IEEE Member.