Research On Blade Impact And Bearing Defects Of Aero-engine On Acoustic Emission Detection

Aero-engine is the core power equipment for safe operation of aircraft.Aero-engine has been in the harsh environment of high temperature,high pressure and heavy load for a long time,and its components are more and more likely to fail,among which the failure of bearing and rotor system is the most common.Based on this,this paper proposes to use acoustic emission technology as the main means to monitor the impact of external objects on Aero-engine blades and bearing defects.And two experimental studies on impact of objects on aero-engine blades and bearing failure were carried out.In the research of aero-engine blade impact,based on the impact energy equivalent method,the pendulum impact experiment was carried out,and the AE signals of the blade under different impact energy were obtained.The time domain and frequency domain characteristics of the impact AE signal are analyzed.The results show that the signal energy and RMS in the characteristic parameters of AE signal.are approximately linear;the ringing count and duration increase with the increase of impact energy,and they are approximately quadratic;with the increase of impact energy,the energy entropy of the wavelet packet of the signal increases.Signal energy,RMS,ringing count,duration and wavelet packet energy entropy have a certain recognition effect on blade impact energy,which can be used as a basis for the recognition of blade impact energy.In the study of common bearing faults of aero-engine,bearing defect experiments were carried out.AE signals and vibration signals of bearing defects under different defect types and rotational speeds were measured.The time domain and frequency domain characteristics of acoustic emission signals and vibration signals were analyzed.The analysis results show that AE signals are sensitive to weak bearing faults and are beneficial to early monitoring of bearing faults.Aiming at the AE signal of bearing,the improved VMD is used to decompose the signal,and the envelope spectrum of the processed signal is analyzed.The experimental signal is processed by this algorithm.And the results show that the improved VMD algorithm can effectively extract bearing fault features.