Fault Diagnosis Technology Of Aero Engine Main Shaft Bearing Based On Acoustic Emission

Rolling bearings are the crucial parts of aeroengine,The factors that reliability and life of aero engine are relation to the operating status of the main shaft bearing.As the structure and functioning of the aeroengine main shaft bearings' characteristics,developing a simple and effective method of fault diagnosis,not only to reduce the occurrences of disasters,but also avoiding the dismantling caused human and material loss,is significant.In this paper,a combination of theoretical and experimental method was utilized,and the following four tasks for rolling bearing failure were carried out.Firstly,studying the rolling bearing fault characteristics,analyzing the type of rolling bearing fault.And a rolling bearing fault simulation testing bed for rolling bearing fault acoustic emission was created.Studying the out race,inner race and the rollers of the rolling bearing,Conducting experiments to get rolling bearing fault acoustic emission signals at different speed condition.Secondly,RMS values,ring count,amplitude,energy,kurtosis parameters at different speeds conditions for different rolling bearing fault were statistically analysed.Combining the parameter of hits in AE signal of rolling bearing fault characteristic frequency analysed statisticly.Finally,the parameter that different fault vibration signal RMS,peak,peak factor and kurtosis were comparatively analysed statisticly in different conditions.Thirdly,according to the rolling bearing fault characteristic frequency,outer ring,inner ring and rolling elements of rolling bearing's single point of failure acoustic emission signals were carried out.The method of combining wavelet transform and envelope analysis was used,extracting rolling bearing fault characteristic frequency,the results showed that the method are effective.And then,studying the empirical mode decomposition(EMD)and Sliding kurtosis algorithm methods for processing acoustic emission signal.As Empirical mode decomposition has adaptive advantage for non-stationary signal processing problems,and thus in terms of rolling bearing acoustic emission signals processing is remarkable.Sliding kurtosis algorithm was then used to extract the impact characteristic components of the signal.The results indicated that the method are effective.Last but not least,for the actual structure of an aero engine characteristics,studying its main bearing testing program,and ground test of aeroengine was executed,obtained acoustic emission signals including main shaft bearing operational conditions.using the method of combining wavelet transform and envelope analysis extracted the bearing fault characteristic frequencies.In this thesis,the methods are certificated effectively in diagnoseing rolling bearing faults,and analysis have been showed that the reliability of diagnosis is well.The analysis methods in this paper can contribute greatly to the aero-engine main shaft bearing fault diagnosis.