A Local TR-MUSIC Algorithm for Damage Imaging of Aircraft Structures.

Area of Science:

• Materials Science and Engineering
• Mechanical Engineering
• Aerospace Engineering

Background:

• Aircraft structural health monitoring (SHM) relies on accurate damage detection.
• Lamb wave-based imaging offers potential for SHM but faces resolution challenges.
• Existing damage imaging techniques struggle with detecting multiple or closely spaced damages.

Purpose of the Study:

• To develop an enhanced damage imaging technique for plate-type structures.
• To improve the resolution and capability of detecting multiple damages using Lamb waves.
• To address the persistent challenge of enhancing damage detection resolution in SHM.

Main Methods:

• Development of a damage imaging technique based on the Time Reversal-MUltiple SIgnal Classification (TR-MUSIC) algorithm.
• Establishment of a transfer matrix using excitation and sensing signals.
• Construction of a TR operator for eigenvalue decomposition and subspace separation.
• Proposal of a local TR-MUSIC algorithm employing a moving time window for enhanced imaging.
• Validation through numerical simulations and experimental testing.

Main Results:

• The local TR-MUSIC algorithm effectively detects multiple damages in plate structures.
• The enhanced algorithm achieves good image quality for damage localization.
• Demonstrated super-resolution capability for detecting damages closer than half the wavelength.

Conclusions:

• The proposed local TR-MUSIC algorithm significantly enhances damage imaging for SHM.
• This technique offers superior performance in detecting multiple and closely spaced damages.
• The super-resolution ability advances the field of high-resolution damage detection in plate structures.