TY - GEN
T1 - Aircraft Structural Strength Verification Based on Cyber-Physical Fusion
AU - Ding, Simeng
AU - Guo, Yangming
AU - Kang, Yan
AU - Wang, Xiaodong
AU - Min, Qiang
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - With the continuous development of aviation technology, the complexity of aircraft structures continues to increase, and higher requirements are placed on their strength test verification. Traditional test verification methods can no longer meet the requirements of new aircraft structures for high precision, real-time performance, and data fusion. This paper studies the application of cyber-physical fusion technology in aircraft structural strength testing, focusing on key technologies such as PINN-based virtual model calibration and improvement, and multi-source heterogeneous data fusion. Through these methods, stress field reconstruction, sensor data fusion noise reduction, and dynamic response display under limited measurement point conditions are achieved, thereby significantly improving the accuracy and efficiency of structural strength verification. The research results provide new technical support for structural reliability assessment, early fault diagnosis, and health management, and contribute to proactive maintenance and life cycle management.
AB - With the continuous development of aviation technology, the complexity of aircraft structures continues to increase, and higher requirements are placed on their strength test verification. Traditional test verification methods can no longer meet the requirements of new aircraft structures for high precision, real-time performance, and data fusion. This paper studies the application of cyber-physical fusion technology in aircraft structural strength testing, focusing on key technologies such as PINN-based virtual model calibration and improvement, and multi-source heterogeneous data fusion. Through these methods, stress field reconstruction, sensor data fusion noise reduction, and dynamic response display under limited measurement point conditions are achieved, thereby significantly improving the accuracy and efficiency of structural strength verification. The research results provide new technical support for structural reliability assessment, early fault diagnosis, and health management, and contribute to proactive maintenance and life cycle management.
KW - cyber-physical systems
KW - data fusion
KW - finite element simulation
KW - intelligent control
KW - ircraft structural strength validation
UR - https://www.scopus.com/pages/publications/105037322536
U2 - 10.1109/PHM-Xian66756.2025.11427804
DO - 10.1109/PHM-Xian66756.2025.11427804
M3 - 会议稿件
AN - SCOPUS:105037322536
T3 - 2025 Global Reliability and Prognostics and Health Management Conference, PHM-Xian 2025
BT - 2025 Global Reliability and Prognostics and Health Management Conference, PHM-Xian 2025
A2 - Wang, Huimin
A2 - Li, Steven
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 16th IEEE Reliability and Prognostics and Health Management Conference, PHM-Xian 2025
Y2 - 10 October 2025 through 12 October 2025
ER -