An Impact Load History Reconstruction Method for Composite Structures Based on FBG Sensing Data and the GCV Principle

Area of Science:

• Materials Science
• Mechanical Engineering
• Aerospace Engineering

Background:

• Accurate load history acquisition is vital for composite aircraft structure damage identification and digital twin development.
• Low sampling rates of quasi-distributed Fiber Bragg Gratings (FBG) can cause signal distortion in impact response.
• Manual selection of regularization parameters limits noise suppression and reconstruction accuracy.

Purpose of the Study:

• To develop a robust method for reconstructing impact load history on composite structures.
• To mitigate signal distortion issues caused by low-rate FBG sampling.
• To overcome limitations of manual parameter selection in impact load reconstruction.

Main Methods:

• Utilized Generalized Cross-Validation (GCV) and Fiber Bragg Grating (FBG) patterns for impact load reconstruction.
• Developed an equivalent expansion technique with discretized time-domain sparse strain sampling.
• Applied Tikhonov regularization to manage the ill-posed nature of the impact frequency response matrix.
• Implemented an adaptive optimization method based on the GCV criterion for parameter selection.

Main Results:

• The proposed GCV-based reconstruction method achieved an average peak relative error of 11.4%.
• An average root mean square error of 0.36 N was obtained for the reconstructed impact load.
• The method effectively enhanced the reconstruction of the overall impact load waveform and transient details, even with low-rate sampling.

Conclusions:

• The developed GCV-based method provides accurate impact load history reconstruction for composite structures.
• This technique offers robust technical support for health monitoring and condition-based maintenance of aircraft structures.
• The synergistic enhancement of waveform profile and transient detail characterization improves structural integrity assessment.