Remote monitoring and fault diagnosis system based on the integration of MAS and LONWORKS technology and internet

Author(s):  
Chong Peng ◽  
Qiang Liu ◽  
Tai Pang
2013 ◽  
Vol 589-590 ◽  
pp. 746-751
Author(s):  
Cong Guo Ma ◽  
Jian Guo Wang ◽  
Ya Zhou Li

This paper presents the design scheme of monitoring management and fault diagnosis of open CNC system based on Internet, the system hardware structure introduces network technology three-tier monitoring mode based on field control layer and process monitoring control layer and remote fault diagnosis layer, the system software design includes CNC system management and monitoring and fault diagnosis. The paper integrates condition monitoring and fault diagnosis and expert system technology into CNC system monitoring and management, and analyzes the requirements of distributed numerical control system, and details description system model of remote monitoring and fault diagnosis system. The practice has proved that the system design of open remote monitoring and fault diagnosis is practicality and feasibility.


2006 ◽  
Vol 27 (1) ◽  
pp. 5-19 ◽  
Author(s):  
Xing Wu ◽  
Jin Chen ◽  
Ruqiang Li ◽  
Weixiang Sun ◽  
Guicai Zhang ◽  
...  

2011 ◽  
Vol 308-310 ◽  
pp. 1353-1356
Author(s):  
Ren Xuan Fu ◽  
Yan Du

Based on existing pipe network monitoring system and start with the concept of The Internet of Things[1], the remote monitoring and fault diagnosis system is designed.It can make the fault diagnosis expert experiences shareable, raise user ability, reduce the system maintenance costs,and improve the management level as well.


2012 ◽  
Vol 588-589 ◽  
pp. 178-184
Author(s):  
Jie Liu ◽  
Fang Xia Hu

A networking and intelligent online monitoring and fault diagnosis system for large-scale rotating machinery is developed according to requirements of an iron & steel enterprise. On the aspect of networking, a mixed structure of C/S and B/S is adopted, and the system integrates local online monitoring and diagnosis, remote monitoring and diagnosis, and remote diagnosis center. On the aspect of intelligent diagnosis, a multi-symptom comprehensive parallel diagnosis technology is adopted based on expert system, neural network and fuzzy logic. Finally, main functional modules and its realization are introduced. Application shows that the system runs normally, and the expected objective is achieved.


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