Aiming at the difficulty of fault diagnosis of rolling bearing in aero-engine mechanical system,the work aims to propose a fault extraction method of rolling bearing based on CEEMDAN-MPE-VMD multi-component screening fusion.The adaptive noise complete empirical mode decomposition(CEEMDAN)was used to decompose the rolling bearing vibration sig-nal measured under the complex transmission path of strong interference environment,and several node components were ob-tained.The first five components(IMF1-IMF5)with larger relative MPE were selected,and then the five components were de-composed by variational mode decomposition(VMD).The first four components(imf1-imf4)with larger MPE of each compo-nent were selected again,and then the four components(imf1-imf4)of these five groups were reconstructed respectively to ob-tain a new(IMF1-IMF5),which was reconstructed with the previous IMF10-IMF14 for envelope demodulation to identify fault feature information.Based on the experimental data of Xichu University and the test data of the rolling bearing test bench,the effectiveness of the vibration signal extraction method was comprehensively verified,and the fault identification was carried out on the data measured by the aero-engine intermediate bearing simulation test bench.The results show that this method can ef-fectively extract the fault features of rolling bearings under simple and complex transmission paths,and can be used as one of the methods to extract the features and carry out diagnosis of aero-engine spindle bearings.
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