Enhanced statistical damage identification using frequency-shift information with tunable piezoelectric transducer circuitry

The frequency-shift-based damage detection method entertains advantages such as global detection capability and easy implementation, but also suffers from drawbacks that include low detection accuracy and sensitivity and the difficulty in identifying damage using a small number of measurable frequencies. Moreover, the damage detection/identification performance is inevitably affected by the uncertainty/variations in the baseline model. In this research, we investigate an enhanced statistical damage identification method using the tunable piezoelectric transducer circuitry. The tunable piezoelectric transducer circuitry can lead to much enriched information on frequency shift (before and after damage occurrence). The circuitry elements, meanwhile, can be directly and accurately measured and thus can be considered uncertainty-free. A statistical damage identification algorithm is formulated which can identify both the mean and variance of the elemental property change. Our analysis indicates that the integration of the tunable piezoelectric transducer circuitry can significantly enhance the robustness of the frequency-shift-based damage identification approach under uncertainty and noise.