Digital Twins Prediction of Crack Growth Life for the Lap Joint Structure Combined with Guided Wave Monitoring Data

doi:10.3901/JME.2024.16.034

Abstract

Abstract: Requirements for the high performance and long service life of aircraft lead to the urgent need for a revolution against traditional structural design and maintenance strategies. In the theoretical framework of the digital twin, an online prediction method of crack growth life for the lap joint structure of aircraft is proposed. The digital twin of the physical structure and its surrogate model is established using the a priori crack growth rule and the finite element model. During the service of the structure, the active guided wave monitoring method is used to monitor the cracks of the actual lap joint structure online. Further, parameters of the crack growth rule of the lap joint structure are corrected by using Bayesian filtering, which is combined in the digital twin for predicting its fatigue crack growth life. The proposed method is validated on the fatigue test of lap joint structures in the aircraft skin. The root means square of the diagnosed crack length is 0.8 mm and the relative error of the predicted fatigue crack growth life is 5% after 80 000 loading cycles, showing the effectiveness of the method.

Key words: lap joint structure, crack extension life prediction, digital twin, guided wave-based structural health monitoring, Bayesian filtering

CLC Number:

V215

CHEN Jian, MENG Yixing, YUAN Shenfang, XU Qiuhui, WANG Hui. Digital Twins Prediction of Crack Growth Life for the Lap Joint Structure Combined with Guided Wave Monitoring Data[J]. Journal of Mechanical Engineering, 2024, 60(16): 34-42.

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