Noise is unavoidable and ever-present in measurements. As a result, signal denoising is a necessity for many scientific and engineering disciplines. In particular, structural health monitoring applications aim to detect often weak anomaly responses generated by incipient damage (such as acoustic emission signals) from background noise that contaminates the signals. Among various approaches, stochastic resonance has been widely studied and adopted for denoising and weak signal detection to enhance the reliability of structural heath monitoring. On the other hand, many of the advancements have been focused on detecting useful information from the frequency domain generally in a postprocessing environment, such as identifying damage-induced frequency changes that become more prominent by utilizing stochastic resonance in bistable systems, rather than recovering the original time domain responses. In this study, a new adaptive signal conditioning strategy is presented for on-line signal denoising and recovery, via utilizing the stochastic resonance in a bistable circuit sensor. The input amplitude to the bistable system is adaptively adjusted to favorably activate the stochastic resonance based on the noise level of the given signal, which is one of the few quantities that can be readily assessed from noise contaminated signals in practical situations. Numerical investigations conducted by employing a theoretical model of a double-well Duffing analog circuit demonstrate the operational principle and confirm the denoising performance of the new method. This study exemplifies the promising potential of implementing the new denoising strategy for enhancing on-line acoustic emission-based structural health monitoring.
Proc. SPIE. 9061, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2014
KEYWORDS: Mathematical modeling, Signal to noise ratio, Data modeling, Scanning electron microscopy, Inverse problems, Transducers, Finite element methods, Damage detection, System integration, Inductance
The piezoelectric impedance-based method for damage detection has been explored extensively for its high sensitivity to
small-sized damages with low-cost measurement circuit which enables remote damage monitoring. While the method
has good potential, the amount of feasible impedance data is usually much less than the number of required system
parameters to accurately identify the damage location/severity via an inverse formulation. This data incompleteness
forms a highly underdetermined problem and because of this numerical ill-conditioning, the predicted damage
parameters will be significantly influenced by unavoidable measurement noise and the accuracy of the base-line model.
In this study, the state of the art of impedance-based damage identification is advanced by incorporating a tunable
piezoelectric circuitry with the structure to enrich the impedance measurements. This piezoelectric circuitry introduces
additional degrees of freedom to the structure and changes the dynamics of the coupled system. By tuning the inductance
value, it is possible to perform various measurements under different system dynamics which reflects the damage effect.
Therefore, if performed systematically, notably increased sets of measurement can be obtained, which will improve the
inverse problem to be less underdetermined. Clearly, we can expect the accuracy and robustness in damage identification
to be significantly enhanced. Numerical case study on localizing damage in a fixed-fixed beam using spectral element
method is performed to demonstrate the effectiveness of the new method for structural damage identification.