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Vol. 168, Issue 4, April 2014, pp. 1-7

 

Bullet

 

An Online Fault Pre-warning System of the Rolling Mill Screw-down Device
Based on Virtual Instrument
 

Qing Bai, * Baoquan Jin, Yan Gao, Hongjuan Zhang

Key Lab of Advanced Transducers and Intelligent Control System, Ministry of Education, Taiyuan University of Technology No. 79, West Yingze Street, Taiyuan, Shanxi, 030024, P. R. China

* E-mail: jbq_007@163.com

 

Received: /Accepted: 7 April 2014 /Published: 30 April 2014

Digital Sensors and Sensor Sysstems

 

Abstract: A traditional off-line screw-down monitoring system performs not well on real-time signal analysis or process, which cannot provide simultaneous fault pre-warning either. A diagnostic monitoring system as well as a remotely accessible graphic user interface is presented in this paper. The main objective of this work is to develop an online and available technique for monitoring the kinetic, hydrodynamic and electrical parameters of the rolling mill screw-down device, and analyze these figures to support online fault pre-warning. A series of transducers are installed in suitable locations to measure parameters decried above including the vibration acceleration of a rolling mill stand, the rolling force of a screw-down device, the stroke of a hydraulic cylinder, the system source pressure, the in-cylinder stress and the output value of an electro-hydraulic servo valve. An industrial personal computer picks up the information transformed by an extra high-speed data acquisition board embedded inside, processes the signals via a software designed by means of Laborary Virtual Instrument Engineering Workbench (LabVIEW) and indicates fault conditions through the graphic user interface. Besides, the data of the overall system can be published over the Internet using LabVIEW Web Server capabilities. The results of experiments suggest that the system works well on real-time data acquisition and online fault pre- warning. The statistics saved contributes to the research of vibration performance and malfunction analysis of a rolling mill.

 

Keywords: Screw-down device, Real-time signal process, Virtual instrument, Web server, Online fault pre-warning.

 

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