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
[1]
Wang Kui-sheng.
Study of the fault diagnoses of flexible wire rope sucker rod pumping unit based on artificial neural network
,
2005
.
[2]
Jonathan Knudsen,et al.
Learning Java
,
2000
.
[3]
Haydn A. Thompson.
Wireless and Internet communications technologies for monitoring and control
,
2004
.
[4]
Yilu Liu,et al.
LAN-based load shedding controller (LSC) for the oil refinery facility
,
2001,
2001 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.01CH37194).
[5]
Luo Xiaobin.
The Technology and Application of Asynchronous Messaging Based on JMS
,
2002
.
[6]
Philip Rousselle.
Implementing the JMS publish/subscribe API
,
2002
.
[7]
James Won-Ki Hong,et al.
WebTrafMon: Web-based Internet/Intranet network traffic monitoring and analysis system
,
1999,
Comput. Commun..