Research on Web Based Remote Monitor and Control System for Grinding Process

2006 ◽  
pp. 1112-1115
Author(s):  
Gui Jie Liu ◽  
Ning Mei ◽  
Jun Zhe Tan
Keyword(s):  
Control System ◽  
Grinding Process ◽  
Web Based ◽  
Remote Monitor ◽  
Monitor And Control System ◽  
And Control ◽  
Monitor And Control

Research on Web Based Remote Monitor and Control System for Grinding Process

2006 ◽  
Vol 532-533 ◽  
pp. 1112-1115
Author(s):  
Gui Jie Liu ◽  
Ning Mei ◽  
Jun Zhe Tan
Keyword(s):  
Control System ◽  
Working Environment ◽  
Work Piece ◽  
Grinding Process ◽  
Skilled Workers ◽  
Web Based ◽  
Remote Monitor ◽  
Java Applet ◽  
Feature Information ◽  
And Control

A web based remote monitor & control system for grinding process is presented. In this system, OPC/Socket drive technology, CAN bus technology, B/S structure, Java Applet and ActiveX etc. are used to realize the remote monitor & control, and grinding processes in different place can be monitored and controlled by remote grinding expert only through browser, so it overcomes the shortage that the grinding quality depends on skilled workers and variants with grinding operators. The data processing and feature releasing method of AE signals in grinding process also be discussed. The grinding state feature information can be updated automatically, and be browsed by remote experts through running the ActiveX in the browser. Therefore, it is of important significance for improving workers’ working environment and work-piece quality.

Intelligent Monitor and Control System for Grinding Process

2006 ◽  
Vol 304-305 ◽  
pp. 535-539 ◽  
Author(s):  
Gui Jie Liu ◽  
Ya Dong Gong ◽  
Wan Shan Wang
Keyword(s):  
Control System ◽  
Nonlinear Modeling ◽  
Grinding Process ◽  
Learning Capability ◽  
Grinding Conditions ◽  
On Line ◽  
Monitor And Control System ◽  
And Control ◽  
Ae Signals ◽  
Monitor And Control

The intelligent monitor and control system for grinding process is proposed in this paper, it utilizes the nonlinear modeling theory and self-learning capability of neural network to setup non-liner mapping relations between grinding conditions and AE signals, and to realize grinding process intelligent monitor and control by picking-up grinding AE signals on line. Grinding quality can be monitored on-line, starting parameters for grinding process can be selected, on-line intelligent adjustment of grinding conditions also can bee realized by using this system.

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