Detection of crack formation and stress distribution for carbon fiber–reinforced polymer specimens through triboluminescent-based imaging. (May 2015)

• Record Type: Journal Article
• Authors: Aich, Nirupam; Kim, Eunho; ElBatanouny, Mohamed; Plazas-Tuttle, Jaime; Yang, Jinkyu; Ziehl, Paul; Saleh, Navid B
• Is Part Of: Journal of intelligent material systems and structures. Volume 26:Number 8(2015:May)
• Page Start: 913
• Page End: 920
• Publication Date: 2015-05
• Subjects: Polymers -- sensor -- structural health monitoring; Smart materials -- Periodicals; Intelligent control systems -- Periodicals; Artificial intelligence -- Periodicals; Matériaux intelligents -- Périodiques; Commande intelligente -- Périodiques; Intelligence artificielle -- Périodiques; 620.11
• DOI: 10.1177/1045389X14535017
• Languages: English
• ISSNs: 1045-389X

Abstract

This article demonstrates the ability of surface-coated triboluminescent materials to detect damage in carbon fiber–reinforced polymer specimens. An experimental protocol was developed to test the efficiency of the triboluminescent-based diagnostic method using carbon fiber–reinforced polymer coupons under combined bending–compression conditions. Luminescence, emitted from the triboluminescent coatings under quasi-static loading, was detected by capturing digital images. We employed image processing software to quantify change in luminescence as a function of triboluminescent concentration. We observed that 10%, 20%, and 30% triboluminescent coating resulted in 25.3, 27.9, and 40.4 (arbitrary units) total luminescence, respectively, which shows a positive correlation of triboluminescent concentration with luminescence. Finite element simulation was also performed to understand the stress and strain distribution and to aid in understanding and correlating light emission regions on the carbon fiber–reinforced polymer coupons under bending deformation. This work represents a step toward the development of a robust technology that employs triboluminescent materials for early damage detection, consistent with theoretical predictions of damage occurrence.