Digital Image Correlation Compatible Mechanoluminescent Skin for Structural Health Monitoring

• Published in: Advanced science 2022-04, Vol.9 (11), p.e2105889-n/a
• Main Authors: Shin, Ho Geun, Timilsina, Suman, Sohn, Kee‐Sun, Kim, Ji Sik
• Format: Article
• Language: English
• Subjects: Algorithms; Alloys; Aluminum alloys; Calibration; crack‐tip HRR field; Deformation; Fingers; mechanoluminescent (ML) quantification; mechanoluminescent skin; Methods; Plastics; Skin; structural health monitoring; Tension tests; trap‐controlled mechanism; Visualization
• ISSN: 2198-3844; 2198-3844
• DOI: 10.1002/advs.202105889

Monitoring structural health using mechanoluminescent (ML) effects is widely considered as a potential full‐field and direct visualizing optical method with high spatial and temporal resolution and simple setup in a noncontact manner. The challenges and uncertainties in the mapping of ML field to effective strain field, however, tend to limit significant commercial ML applications for structural health monitoring systems. Here, however, quantification problems are resolved using the digital image correlation (DIC) method. Specifically, an image containing mechanically induced photon information is processed using a DIC algorithm to measure the strain field components, which enables the establishment of a calibration curve when the ML field is mapped onto the effective strain field using pixel level information. The results show a linear relationship between effective strain and ML intensity despite the plastic flow in ML skin. Furthermore, the calibration curve allows for easy conversion of ML field to effective‐strain field at the crack‐tip plastic zone of the alloy structure, retaining its spatial resolution. The compatibility of ML skin with the DIC algorithm not only enables the quantification of the ML effects of several organic/inorganic ML materials, but may also be useful in elucidating the fundamentals of the trap‐controlled mechanism. The compatibility of mechanoluminescent (ML) skin with the digital image correlation under UV exposure is leveraged to quantify the ML effects in terms of effective strain. The calibration can be executed using the same photographic image. Interestingly, a linear correlation exists despite the plastic flow in ML skin. The quantification extends the ML application from visualizing to quantitative measurement.