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Delamination damage identification of thermoplastic composite pipe based on residual attention Brownian covariance network
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Chuan-yuan PENG1, Qi-ming SHU2, You-wei DU1, Wen SHEN1
Journal of Ship Mechanics | 2026, 30(5) : 779 - 790
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Journal of Ship Mechanics | 2026, 30(5): 779-790
• Structural Mechanics •
Delamination damage identification of thermoplastic composite pipe based on residual attention Brownian covariance network
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Chuan-yuan PENG1, Qi-ming SHU2, You-wei DU1, Wen SHEN1
Affiliations
  • 1.Intelligent Manufacturing College, Qingdao Huanghai University, Qingdao 266427, China
  • 2.School of Shipbuilding and Ocean Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Published: 2026-05-15 doi: 10.3969/j.issn.1007-7294.2026.05.010
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Thermoplastic composite pipes (TCP) have been widely used in marine structures. In this paper, a residual attention Brownian covariance neural network is established to study the damage identification of TCP composite delamination. Firstly, the curvature modes of multiple groups of thermoplastic composite tubes with single damage, multiple damages and different damage degrees were calculated using the finite element method. Then, the delamination damage identification method of thermoplastic composite tubes was discussed. Finally, the residual attention Brownian covariance network model was constructed using the curvature modes as input parameters to identify the delamination damage location and damage degree of TCP. The results show that the damage identification model based on residual attention Brownian covariance network can identify the location and degree of damage. The accuracy of damage location identification is 100%, and the error of damage degree identification is less than 6%. The research results provide a reference for non-destructive testing of marine engineering structures.

thermoplastic composite pipe  /  curvature mode  /  damage identification  /  residual attention network
Chuan-yuan PENG, Qi-ming SHU, You-wei DU, Wen SHEN. Delamination damage identification of thermoplastic composite pipe based on residual attention Brownian covariance network[J]. Journal of Ship Mechanics, 2026 , 30 (5) : 779 -790 . DOI: 10.3969/j.issn.1007-7294.2026.05.010
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Year 2026 volume 30 Issue 5
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Article Info
doi: 10.3969/j.issn.1007-7294.2026.05.010
  • Receive Date：2025-09-11
  • Online Date：2026-07-07
  • Published：2026-05-15
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  • Received：2025-09-11
Affiliations
    1.Intelligent Manufacturing College, Qingdao Huanghai University, Qingdao 266427, China
    2.School of Shipbuilding and Ocean Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
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表12种不同金属材料的力学参数
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Family		 属数
Number of
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Number of
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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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