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Real-time fatigue crack prediction using self-sensing buckypaper and gated recurrent unit
Hyeonho Hwang,송진우,김흥수,Aditi Chattopadhyay 대한기계학회 2023 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.37 No.3
Aircraft is regarded as a collection of modern technologies from throughout all industries. However, it is inevitable to develop defects during its service life. In general, the aircraft has a periodic maintenance period, and is inspected according to a well-established process, for example non-destructive testing. However, the maintenance requires massive time and cost. If an unexpected defect occurs due to external environments before the maintenance cycle returns, it is impossible to prevent subsequent damage. This study proposes a novel realtime fatigue crack prediction method using self-sensing carbon nanotube buckypaper and deep learning algorithm. Carbon nanotube buckypaper was fabricated by the wet method. The physics-informed gated recurrent unit was used to predict real time crack growth. The physicsinformed deep learning model accurately predicted the fatigue crack length. The results showed that the proposed method is promising in detecting the real-time fatigue crack growth of aircraft structure.
Delamination identification of laminated composite plates using measured mode shapes
Yongfeng Xu,Da-Ming Chen,Weidong Zhu,Guoyi Li,Aditi Chattopadhyay 국제구조공학회 2019 Smart Structures and Systems, An International Jou Vol.23 No.2
An accurate non-model-based method for delamination identification of laminated composite plates is proposed in this work. A weighted mode shape damage index is formulated using squared weighted difference between a measured mode shape of a composite plate with delamination and one from a polynomial that fits the measured mode shape of the composite plate with a proper order. Weighted mode shape damage indices associated with at least two measured mode shapes of the same mode are synthesized to formulate a synthetic mode shape damage index to exclude some false positive identification results due to measurement noise and error. An auxiliary mode shape damage index is proposed to further assist delamination identification, by which some false negative identification results can be excluded and edges of a delamination area can be accurately and completely identified. Both numerical and experimental examples are presented to investigate effectiveness of the proposed method, and it is shown that edges of a delamination area in composite plates can be accurately and completely identified when measured mode shapes are contaminated by measurement noise and error. In the experimental example, identification results of a composite plate with delamination from the proposed method are validated by its C-scan image.