A smart composite panel based on piezoelectric sensors

The present study describes the results of a research effort to develop the methodology to detect low-velocity impact events. PVDF piezopolymer sensors and PZT piezoceramic sensors were evaluated for their suitability for detecting potential damage-inducing impact events on lightweight composite skin panels. Three phases of the technology were addressed in this study: fabrication; durability of sensors and their effect upon the strength of host structures, together with the effect of the bonding layer upon sensor responses; and performance of the smart panel under low-velocity impact events, and an analytical model to identify impact location and force.;Several techniques of incorporating the sensors into solid laminated panel were developed. Both types of sensors were successfully mounted on the laminate surface. Durability tests showed that the surface-mounted sensors did not impair performance of the structures. Piezopolymer sensors were found to be capable of monitoring low-velocity impact without affecting the integrity of the host structures and without reducing the sensor performance under static and cyclic loading.;Two piezopolymer sensors were epoxy-bonded to the bottom surface of a cross-ply GR/EP laminate. A smaller steel ball (5.59-gr mass) impactor and a larger impactor (94.5-gr mass) were used as the impactors. With each impactor/panel combination, five different impact locations and four different impact heights were selected. As impact energy was increased for a given impact location, the shape of the sensor output waveform remained consistent but the amplitude of the signal increased.;The system operator was derived by combining the piezoelectric constitutive equation of the piezoelectric sensor with the approximate closed-form solution of the impact event of the composite plate based on the assumed-mode method. The same formulation was used to solve the inverse problem, i.e., to predict impact force and location from the sensor signals. The algorithm is based on the inverse solution of a convolution type of integral equation and uses an iterated Tikhonov regularization method. Comparisons were made with finite element predictions. The algorithm has been shown to be able to predict impact force and location from sensor signals.