Research on identification method of aero-engine bearing fault using acoustic emission technique based on wavelet packet and rough set

As an important supporting component in aero-engine, rolling bearing has an important influence on the safety and reliability of aero-engine, the condition monitoring and fault diagnosis of rolling bearings has become the focus of research. This paper is to build a simple aero-engine experiment platform, using acoustic emission(AE) on-line monitoring system to extract real-time characteristics of rolling bearing, using wavelet packet to decompose the AE signal, and to reconstruct the decomposition coefficients in different frequency bands to obtain the characteristic parameters, using rough set theory to obtain clear and concise decision rules, which can identify the bearing fault types and realize the health management of rolling bearings.