数字孪生机翼损伤模式快速识别与监测方法

To address the problems of complex recognition and poor real-time performance in the process of structural health monitoring of aircraft， a digital twin technology-based damage pattern recognition and prediction method for aircraft wings was proposed. The digital twin structural model of the aircraft wing was constructed using modular technology，and the mapping method of sensor data in the structural digital twin model was established based on probabilistic neural network， forming a fast monitoring process of general digital twin aircraft structural damage pattern. Based on an unmanned aerial vehicle，a rapid damage pattern recognition model of its wings was developed. The results showed that the damage pattern identification accuracy of the digital twin recognition model for aircraft structures reached over 96%，which could complete the dynamic trajectory planning task.