STRAIN-SENSING SMART SKIN FOR STRUCTURAL HEALTH MONITORING
Doctor of Philosophy
Over the past twenty years, many structural health monitoring strategies and damage detection techniques/methods have been proposed. Traditional technologies used for measuring strain, such as resistance strain gages, can monitor only at discrete locations and along specific directions, and have limited ability to measure strains on small length scales. Optical fiber sensors and more specifically fiber Bragg grating (FBG) sensors are also widely used in health monitoring of structures, offering strain and temperature readings. However, practical issues, such as deployment of the optical fibre to the structure and connectors and the high cost of the FBGs, need to be addressed. Some emerging full-filed non-contact strain sensing techniques, such as interferometric techniques, non-interferometric techniques and Raman spectroscopy techniques, have other limitations. A non-contact, full-filed strain sensing technique is needed to perform fast Structural Health Monitoring on structures. In this thesis, three generations of a novel non-contact strain measurement technology is developed using raw HiPco single-walled carbon nanotubes (SWCNTs) and different polymers. This approach exploits the characteristic short-wave infrared fluorescence signatures of semiconducting SWCNTs and the systematic shifts of their fluorescence wavelengths when the nanotubes are axially strained. A strain-sensing smart skin (S4) is prepared by coating the surface to be monitored with a thin polymeric film containing well dispersed SWCNTs. Strain in the substrate is transmitted through the polymer to the nanotubes, causing systematic and predictable spectral shifts of the nanotube near-infrared fluorescence peak wavelengths. This promising new method should allow quick and precise strain measurements at any position and along any direction of the substrate. The developed S4 technology has also been applied on pre-damaged specimens to perform 2D strain sensing and damage identification.