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Intelligent identification method for aging state of viscoelastic sandwich structure based on SSA-VMD and ANFIS
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Jinxiu QU1, Xiaowei SHI1, Changquan SHI2, Jiaqi HUANG1, Yumei BAI1, Jiayan WU1, Fei KE1, Wei CAO1
Journal of Vibration Engineering | 2025, 38(10) : 2339 - 2349
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Journal of Vibration Engineering | 2025, 38(10): 2339-2349
Intelligent identification method for aging state of viscoelastic sandwich structure based on SSA-VMD and ANFIS
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Jinxiu QU1, Xiaowei SHI1, Changquan SHI2, Jiaqi HUANG1, Yumei BAI1, Jiayan WU1, Fei KE1, Wei CAO1
Affiliations
  • 1.School of Mechatronic Engineering, Xi’an Technological University, Xi’an 710021, China
  • 2.State Key Laboratory for Manufacturing System Engineering, Xi’an Jiaotong University, Xi’an 710049, China
doi: 10.16385/j.cnki.issn.1004-4523.202308028
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Aiming at the difficulties that the vibration response signal of the viscoelastic sandwich structure is strongly non-stationary and the change of vibration response signal caused by the change of aging state is weak, this paper proposes an intelligeat identification method for the aging state of the viscoelastic sandwich structure based on sparrow search algorithm (SSA) optimized variational mode decomposition (VMD) and adaptive neuro-fuzzy inference system (ANFIS）. The vibration response signals of different aging states of the viscoelastic sandwich structure are decomposed by the parameter-optimized VMD, and several intrinsic mode functions (IMFs) are obtained； The permutation entropy (PE) features of the obtained IMF components are computed, which are used to reflect the structural aging state change； The obtained permutation entropy features are constructed into feature vectors as inputs of ANFIS to realize the aging state intelligent iclentification of viscoelastic sandwich structure. The effectiveness of the method was verified through experiments, and compared with empirical mode decomposition (EMD) and ANFIS, parameter optimized VMD and radial basis function neural network (RBFNN) methods. The results show that the proposed method in this paper can more accurately identify the aging state of viscoelastic sandwich structure.

viscoelastic sandwich structure  /  variational mode decomposition  /  feature extraction  /  adaptive neuro-fuzzy inference system  /  intelligent recognition of aging state
Jinxiu QU, Xiaowei SHI, Changquan SHI, Jiaqi HUANG, Yumei BAI, Jiayan WU, Fei KE, Wei CAO. Intelligent identification method for aging state of viscoelastic sandwich structure based on SSA-VMD and ANFIS[J]. Journal of Vibration Engineering, 2025 , 38 (10) : 2339 -2349 . DOI: 10.16385/j.cnki.issn.1004-4523.202308028
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Year 2025 volume 38 Issue 10
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Article Info
doi: 10.16385/j.cnki.issn.1004-4523.202308028
  • Receive Date：2023-08-14
  • Online Date：2026-02-04
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  • Received：2023-08-14
  • Revised：2023-11-10
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    1.School of Mechatronic Engineering, Xi’an Technological University, Xi’an 710021, China
    2.State Key Laboratory for Manufacturing System Engineering, Xi’an Jiaotong University, Xi’an 710049, China
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表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
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Genus		 种数
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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