Intelligent fault diagnostic system based on RBR for the gearbox of rolling mills

doi:10.1007/s11465-010-0118-6

Front Mech Eng Chin

2010, Vol. 5

Issue (4) : 483-490 https://doi.org/10.1007/s11465-010-0118-6

RESEARCH ARTICLE

Intelligent fault diagnostic system based on RBR for the gearbox of rolling mills

Lixin GAO(

), Lijuan WU, Yan WANG, Houpei WEI, Hui YE

College of Mechanical Engineering and Applied Electronics Technology, Beijing University of Technology, Beijing 100124, China

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Abstract

This paper presents an intelligent system that is necessary for diagnostic accuracy and efficiency in the iron and steel industry. A rule-based reseaning (RBR) intelligent diagnostic system has been developed based on many successful diagnostic applications. It can solve the difficulty in knowledge acquisition and has more precision. Its application results prove that the usability of the system is good and it will increasingly attain perfection.

Keywords rule-based reasoning fault diagnosis intelligent system gear box

Corresponding Author(s): GAO Lixin,Email:gaolixin@bjut.edu.cn

Issue Date: 05 December 2010

Cite this article:

Lixin GAO,Lijuan WU,Yan WANG, et al. Intelligent fault diagnostic system based on RBR for the gearbox of rolling mills[J]. Front Mech Eng Chin, 2010, 5(4): 483-490.

URL:

https://academic.hep.com.cn/fme/EN/10.1007/s11465-010-0118-6
https://academic.hep.com.cn/fme/EN/Y2010/V5/I4/483

Fig.1 Workflow of intelligent diagnostic system

Fig.2 Intelligent diagnostic system framework

Tab.1 Inference rules table

Fig.3 Transmission chain map of high-speed wire mill equipment
(? measuring point location)

Fig.4 Peak trends of a high-speed gear box input points in a rolling mill in August

Fig.5 Probability density at 19’lock on August 15, 2008

Fig.6 Self-relevant map at 19 o’lock on August 15, 2008

Fig.7 Amplitude spectrum at 19 o’clock on August 15, 2008

Fig.8 Waterfall map of gear box input points level in a high-speed rolling mill

Fig.9 Intelligent diagnosis result

Fig.10 Photo in one fault diagnosis

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