Quantitative monitoring of icing on CFRP laminate with guided wave combining forward modeling and inverse characterization

Tian, Yuan1; Duongthipthewa, Anchalee2; Chen, Qi3; Guo, Haotian1,5; Liu, Menglong4,6; Zhang, Jifeng1; Zhou, Limin2

2024-02-01

10.1177/14759217231222544

STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL   影响因子和分区

1475-9217

1741-3168

Aircraft icing is one of the critical factors for flight safety. Timely and accurate monitoring of in-flight ice accretion is essential for flight systems to take immediate and effective action to significantly improve the efficiency of subsequent de-icing processes and ensure flight safety. Since carbon fiber reinforced polymer (CFRP) are now widely used in the aviation industry, the study of ice accretion on the surfaces of CFRP with anisotropic properties is of great importance. In this work, a three-dimensional frequency domain finite element model for icing CFRP laminate is first established, via which the mechanism of mode conversion of ultrasonic guided waves (UGWs) at different ice layer thicknesses is quantitatively analyzed. Then, the time-domain finite element simulation was performed, from which the time-frequency domain spectrogram of the acquired UGW signal is obtained by short-time Fourier transform (STFT). The extracted frequency-time-of-flight (ToF) curve of the signal via STFT shows high agreement with the theoretical results, which confirms the influence of icing on UGW propagation. Finally, numerous experiments with bonded lead zirconate titanate wafers to excite and acquire UGWs are conducted with different ice layer thicknesses and lengths on CFRP. The extracted frequency-ToF curves of UGW signals are used as input to a two-layer feedforward artificial neural network (ANN) to accurately evaluate the length and thickness of the ice layer. The high reliability of this method with ANN is confirmed, which shows the potential of the proposed UGW-based method for quantitative monitoring of icing length and thickness on aircraft CFRP laminate.

Aircraft icing ice detection ultrasonic guided wave finite element simulation artificial neural network

SCI ; EI

英语

其他

National Natural Science Foundation of China["12072141","52105142"] ; National Key R&D Program of China[2022ZD0117302] ; Basic and Applied Basic Research Foundation of Guangdong Province[2023A1515011032]

Engineering ; Instruments & Instrumentation

Engineering, Multidisciplinary ; Instruments & Instrumentation

WOS:001162824500001

SAGE PUBLICATIONS LTD

ENGINEERING

Web of Science

1.Harbin Engn Univ, Coll Aerosp & Civil Engn, Harbin, Peoples R China
2.Southern Univ Sci & Technol, Sch Syst Design & Intelligent Mfg, Shenzhen, Peoples R China
3.China State Shipbuilding Corp Ltd, Res Inst, Harbin, Peoples R China
4.Harbin Inst Technol, Sch Mech Engn & Automat, Shenzhen, Peoples R China
5.Harbin Engn Univ, Coll Aerosp & Civil Engn, Harbin 150001, Hei Longjiang, Peoples R China
6.Harbin Inst Technol, Sch Mech Engn & Automat, Shenzhen 518055, Guangdong, Peoples R China

Tian, Yuan,Duongthipthewa, Anchalee,Chen, Qi,et al. Quantitative monitoring of icing on CFRP laminate with guided wave combining forward modeling and inverse characterization[J]. STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL,2024.

Tian, Yuan.,Duongthipthewa, Anchalee.,Chen, Qi.,Guo, Haotian.,Liu, Menglong.,...&Zhou, Limin.(2024).Quantitative monitoring of icing on CFRP laminate with guided wave combining forward modeling and inverse characterization.STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL.

Tian, Yuan,et al."Quantitative monitoring of icing on CFRP laminate with guided wave combining forward modeling and inverse characterization".STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL (2024).