Digital Image Correlation Compatible Mechanoluminescent Skin for Structural Health Monitoring

Area of Science:

• Materials Science
• Optical Engineering
• Mechanical Engineering

Background:

• Mechanoluminescent (ML) effects offer a promising noncontact method for full-field structural health monitoring.
• Current limitations in mapping ML fields to strain fields hinder commercial applications.

Purpose of the Study:

• To resolve quantification challenges in ML-based structural health monitoring.
• To establish a reliable method for converting ML intensity to effective strain fields.

Main Methods:

• Utilized digital image correlation (DIC) to process images of ML emissions.
• Developed a pixel-level calibration curve mapping ML intensity to effective strain.
• Applied the method to alloy structures, including crack-tip plastic zones.

Main Results:

• Demonstrated a linear relationship between effective strain and ML intensity, even with plastic deformation.
• Successfully converted ML fields to accurate effective strain fields with retained spatial resolution.
• Validated the compatibility of ML materials with the DIC algorithm.

Conclusions:

• The DIC-based quantification method overcomes previous limitations in ML structural health monitoring.
• This approach enables accurate strain mapping and has potential for elucidating ML material mechanisms.
• The findings pave the way for broader commercial adoption of ML for structural integrity assessment.