This paper investigates a new low-power structural health monitoring (SHM) strategy where fiber Bragg grating (FBG) rosettes can be used to continuously monitor for changes in a host structure’s principal strain direction, suggesting damage and thus enabling the immediate triggering of a higher power acoustic emissions (AE) sensor to provide for better characterization of the damage. Unlike traditional “always on” AE platforms, this strategy has the potential for low power, while the wireless communication between different sensor types supports the Internet of Things (IoT) approach. A combination of fiber-optic sensor rosettes for strain monitoring and a fiber-optic sensor for acoustic emissions monitoring was attached to a sample and used to monitor crack initiation. The results suggest that passive principal strain direction monitoring could be used as a damage initiation trigger for other active sensing elements such as acoustic emissions. In future work, additional AE sensors can be added to provide for damage location; and a strategy where these sensors can be powered on periodically to further establish reliability while preserving an energy efficient scheme can be incorporated.
Use of carbon fiber reinforced polymers (CFRPs) presents challenges because of their complex manufacturing processes and different damage mechanics in relation to legacy metal materials. New monitoring methods for manufacturing, quality verification, damage estimation, and prognosis are needed to use CFRPs safely and efficiently. This work evaluates the development of intelligent composite materials using integrated piezoelectric sensors to monitor the material during cure and throughout service life. These sensors are used to propagate ultrasonic waves through the structure for health monitoring. During manufacturing, data is collected at different stages during the cure cycle, detecting the changing material properties during cure and verifying quality and degree of cure. The same sensors can then be used with previously developed techniques to perform damage detection, such as impact detection and matrix crack density estimation. Real-time damage estimation can be combined with prognostic models to predict future propagation of damage in the material. In this work experimental results will be presented from composite coupons with embedded piezoelectric sensors. Cure monitoring and damage detection results derived from analysis of the ultrasonic sensor signal will be shown. Sensitive signal parameters to the different stimuli in both the time and frequency domains will be explored for this analysis. From these results, use of the same sensor networks from manufacturing throughout the life of the composite material will demonstrate the full life-cycle monitoring capability of these intelligent materials.