Inter-shaft bearing is an important component of dual-rotor aeroengine and it is difficult to extract fault characteristics and identify a fault type. Therefore, the paper has proposed a method (CCF-Complexity-VMD-SVD) combining information fusion, Complexity parameter of Hjorth parameters, variational mode decomposition (VMD), and singular value decomposition (SVD). Firstly, to fully embody fault characteristic information, the method has established the cross-correlation function (CCF) of homologous acceleration information from the casing of one of the aeroengines (acceleration signals collected from the same section at the same moment in orthogonal directions) to blend homologous information, reinforce fault characteristic components, and lessen the influence of noise. Secondly, considering the great influence of signal complexity on the extraction of fault characteristics and the Complexity parameter of Hjorth parameters can express the complexity of signals better, the Complexity parameter of Hjorth parameters is placed into the fault characteristic extraction of inter-shaft bearing. The Complexity parameter is applied to optimize the number of layers and central frequency of VMD. Thirdly, signals are denoised through SVD to further lessen the influence of noise on characteristic extraction. Finally, frequency spectrum (FS) of signal denoised is used to make characteristic extraction and fault identification of compound faults of inter-shaft bearing. The result of comparative analysis with other methods has further illustrated the proposed method CCF-Complexity-VMD-SVD that can actualize the effective characteristic extraction of compound faults and precise identification in the early stage of fault based on vibration signals from casing of aeroengine. The performance of engineering appliance of the proposed method has been further verified through fault analysis of disassembly for the aeroengine.
