Generalized variational mode decomposition for interlayer slipping detection of viscoelastic sandwich cylindrical structures

Abstract

The viscoelastic sandwich cylindrical structure (VSCS) is widely applied in aerospace, transportation, etc. Its health is closely related to the security of its own service and the entire set of equipment. Therefore, it is very important to detect its operating state. With a focus on the difficulty of weak feature extraction and the lack of efficient interlayer slipping detection indexes for the VSCS, this paper proposes a generalized variational mode decomposition (GVMD) method to extract the weak feature of the VSCS, and constructs a detection index to identify interlayer slipping fault. To this end, first, a GVMD method is proposed to decompose the original signal into a set of band-limited components (called variational mode functions, VMFs) of interest by taking full advantage of prior information such as spectral locations and bandwidths. Then, the vibration signals from the symmetric positions of the VSCS are decomposed by GVMD to extract the VMFs as expected. Finally, the interlayer slipping detection index, namely the normalized energy of the VMFs, is constructed to identify the interlayer slipping fault. And the interlayer slipping symptoms are explored. The effectiveness of GVMD and the proposed detection index is verified by the simulation and the experiment. The results show that: (1) compared with VMD and complementary ensemble empirical mode decomposition, GVMD can expectedly extract feature components (including weak feature components) owing to its excellent performance. (2) The proposed detection index can effectively identify the interlayer slipping fault of the VSCS, and the frequency components near 2× are sensitive to interlayer slipping fault.

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