Real-Time Wing Deformation Monitoring via Distributed Fiber Bragg Grating and Adaptive Federated Filtering.

Area of Science:

• Aerospace Engineering
• Optical Sensing
• Control Systems

Background:

• Distributed transfer alignment in flight is challenged by wing deformation, impacting accuracy and stability.
• Existing methods struggle with complex flight dynamics and environmental factors affecting alignment.
• Inertial Measurement Units (IMUs) are crucial for navigation but susceptible to errors in dynamic environments.

Purpose of the Study:

• To develop a novel wing-distributed transfer alignment method using Fiber Bragg Gratings (FBGs).
• To improve the accuracy and stability of alignment for IMUs in complex flight scenarios.
• To address limitations in traditional alignment techniques caused by wing deflection and deformation.

Main Methods:

• Established a flexural deformation model utilizing FBGs to monitor wing deformation.
• Developed coupling angle and dynamic lever arm models to account for motion parameters.
• Derived a motion parameter relationship model between main and sub-nodes.
• Proposed and implemented a federated adaptive filter, including an allocation coefficient-based and an updated version.

Main Results:

• The federated adaptive filter with allocation coefficients enhanced IMU pitch angle accuracy by 66.38% and position estimation by 75.67%.
• Improved accuracy in east and sky directions for arm estimation was observed.
• The updated federated adaptive filter boosted sub-IMU pitch angle accuracy by 76.72% and position estimation by 63.51% compared to traditional methods.

Conclusions:

• The proposed FBG-based wing-distributed transfer alignment method significantly improves IMU accuracy and stability.
• Federated adaptive filtering algorithms offer superior performance in complex flight environments.
• This approach provides a robust solution for enhancing navigation system reliability in aerospace applications.