An algorithm for multi-damage size estimation of composite laminates.

Area of Science:

• Materials Science
• Mechanical Engineering
• Non-Destructive Testing

Background:

• Accurate localization and size estimation of composite damage are critical for evaluating material performance.
• Existing methods face challenges in precisely identifying multiple damage sites and their extents.

Purpose of the Study:

• To develop and validate a new methodology for the size estimation of multi-damage in composite laminates.
• To enhance the accuracy of damage localization and boundary identification using Lamb wave technology.

Main Methods:

• Excitation of the pure A0 mode of Lamb waves to mitigate dispersion and multi-modal effects.
• Utilizing a Bayesian-hybrid localization algorithm, incorporating damage reconstruction and modified delay-and-sum (MDAS) for damage identification.
• Employing an adaptive Gaussian mixture model (based on AIC and BIC) to refine damage boundary points and remove outliers.

Main Results:

• The methodology successfully identified and localized multiple damage sites within composite laminates.
• Accurate estimation of damage boundaries was achieved through convex enveloping of identified points.
• Numerical simulations and experimental validation confirmed the method's effectiveness.

Conclusions:

• The proposed Lamb wave-based technique provides an accurate and reliable approach for multi-damage localization and size estimation in composite laminates.
• This method offers significant potential for improving composite performance evaluation and structural health monitoring.