Dissertation > Aviation, aerospace > Aviation > Aeronautical Manufacturing Technology > Aero-engine manufacturing > Fault Analysis and

Study of Aero-engine Intelligent Monitoring Based on Knowledge Discovery

Author WangZuo
Tutor LiYanJun
School Nanjing University of Aeronautics and Astronautics
Course Safety Technology and Engineering
Keywords Aero-engine Spectroscopy knowledge discovery Bayesian networks Intelligent monitoring
CLC V263.6
Type Master's thesis
Year 2011
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Aero-engine plays a vital role in the process of secure flight, Aero-engine Fault Maintenance Technology has been rapid developed in recent years. For the maintenance of the engine can be received timely and the faults of engine can be predicted accurately,we need to introduce oil monitoring technology, combine advanced information fusion technology and knowledge discovery methods effectively, monitor the status of Aero-engine omni-directionally and diagnose the fault accurately. Aero-engine monitoring system becomes to informationize and intelligentize is the irresistible general trend of aviation maintenance industry.In this paper, knowledge discovery methods such as rough sets, decision trees and Bayesian networks are introduced. Meantime, XRF spectroscopy and microscopy-based particle recognition technology are studied. Integrating spectroscopy and particle identification technology, air engine failure data sets are collected. Then, engine wear fault decision optimization was conducted using rough set theory, and fault diagnosis result and repairing advice are gotten by Bayesian network. The knowledge discovery was introduced into engine condition monitoring system to improve diagnosis speed and accuracy. Finally, intelligent aircraft engine monitoring system based on knowledge discovery was designed.

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