This is an exploratory investigation on the self-sensing capabilities of nano-enriched glass/fibre laminates for damage detection purposes through changes in the dynamic responses, which are estimated by measuring the changes in voltage due to a dynamic strain. The deformation of the nano-enriched structure introduces changes in the resistance/voltage of the nanocomposites. The measured voltage signals contain information of the vibratory response of the laminated beam. This research uses a vibration-based data driven methodology for damage detection applied for the estimated vibratory signals using the conductivity properties of the embedded nano-particles. The structure considered in this study is a glass/fibre laminated beam enriched with carbon black nanoparticles (CB). The structure is subjected to a direct electric current and the voltage signal is measured. The vibration based monitoring method used is generally based on singular spectrum analysis applied on the estimated vibratory response. The voltage response signal is divided into a certain number of principal components which contain the oscillatory components distributed by their content of variance in the voltage signal. The components with more variance are used to define a reference state based on the status of the healthy structure. Consequently, the estimated vibratory signals from beams with a simulated damage are compared to the healthy state which eventually results in the damage detection procedure. The damage was simulated firstly by adding an additional mass on the beam tip and secondly by drilling a hole on the beam tip. The results demonstrate the potential for using the voltage estimated vibratory signals for self-sensing damage detection purposes in carbon nano-enriched glass/fibre structures.
- vibration-based structural health monitoring
- Damage assessment
- Composite materials
- singular spectrum analysis
- smart materials