A Density Clustering RAPID Based on an Array-Compensated Damage Index for Quantitative Damage Diagnosis.

Area of Science:

• Engineering
• Materials Science
• Non-destructive Testing

Background:

• Structural Health Monitoring (SHM) is crucial for metal-connected structures.
• Guided wave array-based SHM offers promising damage diagnosis capabilities.
• The Reconstruction Algorithm for Probabilistic Inspection (RAPID) is a key damage localization tool.

Purpose of the Study:

• To propose a novel density clustering RAPID algorithm.
• To enhance damage index adaptivity for sensor array variations.
• To improve the accuracy of damage localization and quantitative diagnosis.

Main Methods:

• Developed a new, array-compensated damage index and probability distribution function.
• Applied density clustering to the RAPID imaging matrix.
• Validated the method through experimental testing on a stiffened aluminum plate.

Main Results:

• The proposed method successfully achieved damage localization.
• Quantitative damage diagnosis was enabled by the new approach.
• Experimental results confirmed the effectiveness of the array-compensated damage index.

Conclusions:

• The density clustering RAPID with an array-compensated damage index enhances SHM performance.
• This method provides accurate damage localization and quantitative assessment for metal structures.
• The approach offers a more robust solution for structural integrity monitoring.