This article investigates the role of ambient temperature in causing changes to the structural wave propagation, as sensed by piezoelectric transducers, in a newer perspective. A novel approach is proposed to compensate the influence of temperature on piezo-sensor response using both analytical models and numerical simulations. Parametric studies using numerical simulations for plates with surface-mounted piezoelectric transducers establish linear functional relationship between change in sensor signals and specific combination of material properties, within certain temperature range. A numerical temperature compensation model is developed based on this functional relationship to reconstruct piezosensor signals at elevated temperatures. Matching pursuit-based signal analysis and reconstruction schemes are used in this study. Practical efficacy of the compensation model is tested for metallic structures with both simple and complex geometries. Model-based reconstruction of first wave packets in the sensor signals is found to match quite well with the experimental measurements. Performance of the proposed compensation model is also found to be at par with the existing state-of-art temperature compensation methods. A very limited set of baseline sensor data is required to estimate unknown model parameters, making this approach to be efficient and practically useful. The output of the compensation model is also used to obtain an accurate estimate of damage location in a structure under varying ambient temperature environments.

The role of the adhesive layer on PZT-induced Lamb wave propagation in structures exposed to elevated temperatures is presented in this article. Both experiments and numerical simulations were performed to study the effects of the adhesive layer on sensor signal at elevated temperatures. Experimentally, signals from PZT transducers with different adhesive thicknesses (40 and 120 μm) were investigated up to 500 kHz. In model simulations, the spectral element package (PESEA), which was developed previously, was adopted to simulate the test results. The simulations agreed with the experimental data quite well. Parametric studies were was then performed using PESEA to evaluate the effect of adhesive layer on PZT-induced Lamb wave propagation at elevated temperatures as compared to other mechanical properties of the host structure and PZT materials; these studies revealed that the stiffness change of adhesive layer due to temperature is the most influential parameter for the change in sensor signals as compared to other mechanical properties, and that the thickness of the adhesive layer can affect a sensor signal in a different manner at elevated temperatures. This study shows PESEA can reasonably simulate the adhesive layer effect at elevated temperatures and hence can be a useful tool for understanding the behavior of Lamb wave propagation generated by adhesively bonded PZTs on structures.

An investigation was performed to develop a damage classification method to characterize sensor data from built-in piezoelectric actuators on laminated composites in terms of matrix micro-cracking and delamination. Traditional signal processing techniques (time-domain analysis and short-time Fourier transform) combined with Gaussian discriminant analysis were proposed to characterize damage in composite plates in this study. Composite coupons of different layup configurations with surfaced mounted arrays of piezoelectric actuators and sensors were subjected to cyclic loading to induce matrix micro-cracking and delamination. Sensor data as well as X-ray images were acquired through the coupon's life. These experimental data were used to train a classifier as well as test the performance and robustness of the learned model. Classification performance was measured via 75-25 holdout and leave-one-sample-out cross-validation. Results show that the proposed method has a misclassification rate of 21%, with high precision and recall values, and it is sensitive to layup configuration.