Abstract
Large flue gas turbine unit is the key equipment in Catalytic Cracking unit of oil-fining plant and it plays an important role in energy saving. As operating in variable condition and high temperature harsh environment, the fault rate of the unit is relatively high. Once faulty happens, enormous economic loss will be caused so it is very important to make condition monitoring and diagnosis. The remote monitoring and diagnosis technology is a new fault diagnosis mode combining with computer technology, communication technology and fault diagnosis technology. Making large flue gas turbine unit as research object, this paper introduces different modes of condition monitoring and diagnosis system, then elaborates overall structure design of the remote monitoring and diagnosis platform constructed, and analyses application of the platform for the unit in detail. The platform can take full advantage of technical support and data sharing to perform remote monitoring and fault diagnosis as well as prediction effectively, improve success rate of fault diagnosis for the unit greatly, and provide technical means to achieve predictive maintenance for large unit.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
WANG **ao-sheng, QU Liang-sheng, ZHAO Bo, LI Yi-pu.(1997) Research on the impact of bearing stability on the vibration from overhung flue gas turbine.Chemical Engineering & Machinery, 24(5): 293-297
FEI Guo-qin. (2003) The factors that impact long period, safe operation of flue gas turbine and its analysis. Petrochemical equipment technology, 24 (5): 24-28
XIE Zhi-jiang, GUO Yu-**g.(2006) Research on the distributed remote fault diagnosis platform. Modern Manufacturing Engineering, (7):103-105
CHEN **ao-ming, WU jia-ming, KONG Qing-fu, YU Guang-fu, YANG Yong-hong. (2006) Design on building the modern monitoring and diagnosis platform for warship power plant. Ship & Ocean Engineering, (3): 90-93
G.K. Singh and Sad Ahmed Saleh.AI Kazzaz.(2003)Induction machine drive condition monitoring and diagnostic researcha survey. Electric Power Systems Research, 64(2): 145-158
Min-Chun Pan, Po-Ching Li, Yong-Ren Cheng. (2008) Remote online machine condition monitoring system. Measurement, (41):912-921
Zhong Binglin, Huangren. (2007) Mechanical Fault Diagnostic Theory (3rd Edition), Bei**g: China Machine Press
Eduardo Gilabert, Aitor Arnaiz. (2006) Intelligent automation systems for predictive maintenance: A case study. Robotics and Computer-Integrated Manufacturing, (22):543-549
Jay Lee, Jun Ni, Dragan Djurdjanovic, Hai Qiu, Haitao Liao.(2006) Intelligent prognostics tools and e-maintenance. Computers in Industry, (57):476-489
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag
About this paper
Cite this paper
Tao, C., **ao-li, X., Shao-hong, W., San-peng, D. (2010). The Construction and Application of Remote Monitoring and Diagnosis Platform for Large Flue Gas Turbine Unit. In: Kiritsis, D., Emmanouilidis, C., Koronios, A., Mathew, J. (eds) Engineering Asset Lifecycle Management. Springer, London. https://doi.org/10.1007/978-0-85729-320-6_67
Download citation
DOI: https://doi.org/10.1007/978-0-85729-320-6_67
Publisher Name: Springer, London
Print ISBN: 978-0-85729-321-3
Online ISBN: 978-0-85729-320-6
eBook Packages: EngineeringEngineering (R0)