NDLI: Implementation of Network-computing and NN based Remote Real-time Oil Well Monitoring System

Content Provider	IEEE Xplore Digital Library
Author	Li Hongsheng Wang Yu Ding Yongzhong Peng Zhongxiao
Copyright Year	2005
Description	Author affiliation: Sch. of Autom., Wuhan Univ. of Technol. (Li Hongsheng; Wang Yu; Ding Yongzhong)
Abstract	This paper introduces a real-time oil well monitoring system based on network computing and neural network (NN) technologies. In the system, some enterprise computing techniques such as browser/server Web mode, JMS, message-oriented middleware (MOM) and Java Applet are employed. In addition, GPRS wireless communication is used to achieve remote transmission of oil well data. This scheme makes adopts Java Applet that operates at client side (Web browser) to receive messages "pushed" by server through JMS (Java Message Service). In this way, server and client are able to communicate in time so that client side can reflect the real-time oil well data and the fault diagnosis result. In remote monitoring center, the fault diagnosis station takes the responsibility for the fault detection and diagnosis of oil pumping units by means of neural networks and evolutionary computation. This solution accomplishes network share of oil well information, improves the efficiency of system development. The system has already been applied successfully to an oil field, and has got the anticipated results
Starting Page	1810
Ending Page	1814
File Size	2263681
Page Count	5
File Format	PDF
ISBN	0780394224
DOI	10.1109/ICNNB.2005.1614978
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-10-13
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Real time systems Java oil well monitoring Browser/Server mode Ground penetrating radar fault diagnosis network computing Neural Networks Petroleum Fault diagnosis Network servers JMS Message-oriented middleware Neural networks Computer networks Remote monitoring
Content Type	Text
Resource Type	Article

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