Title :
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
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;
Conference_Titel :
Wireless Communications and Mobile Computing Conference (IWCMC), 2013 9th International
Conference_Location :
Sardinia
Print_ISBN :
978-1-4673-2479-3
DOI :
10.1109/IWCMC.2013.6583757