Vibration sensor based intelligent fault diagnosis system for large machine unit in petrochemical industry

Author

Qing-hua Zhang ; Aisong Qin ; Lei Shu ; Guoxi Sun ; Longqiu Shao

Author_Institution

Guangdong Petrochem. Equip. Fault Diagnosis Key Lab., Guangdong Univ. of Petrochem. Technol., Maoming, China

fYear

2013

fDate

1-5 July 2013

Firstpage

1376

Lastpage

1381

Abstract

In this paper, to satisfy the need of fault monitoring, dynamic real time vibration monitoring and vibration signal analysis for large machine unit in petrochemical industry, which cannot realize real-time, online and fast fault diagnosis, an intelligent fault diagnosis system is developed using artificial immune algorithm and dimensionless indicators, innovated with a focus on reliability, remote monitoring and practicality, and be applied to the Third Catalytic Flue Gas Turbine in a petrochemical enterprise and have got good effects.

Keywords

artificial immune systems; computerised monitoring; fault diagnosis; fuel processing industries; knowledge based systems; machinery; petrochemicals; production engineering computing; production equipment; sensors; signal processing; vibrations; artificial immune algorithm; catalytic flue gas turbine; dimensionless indicators; dynamic real time vibration monitoring; fault monitoring; large machine unit; petrochemical enterprise; petrochemical industry; reliability; remote monitoring; vibration sensor based intelligent fault diagnosis system; vibration signal analysis; Artificial intelligence; Fault diagnosis; Market research; Monitoring; Petrochemicals; Real-time systems; Vibrations; artificial immunity algorithm; dimensionless indicators; fault diagnosis; immune detector; time-domain vibration signals;

fLanguage

English

Publisher

ieee

Conference_Titel

Wireless Communications and Mobile Computing Conference (IWCMC), 2013 9th International

Conference_Location

Sardinia

Print_ISBN

978-1-4673-2479-3

Type

conf

DOI

10.1109/IWCMC.2013.6583757

Filename

6583757