Mr. Rakesh Malladi Profile

Rakesh Malladi

at Rice Univ

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Proceedings Article | 9 March 2014 Paper

Modelling ultrasound guided wave propagation for plate thickness measurement

Rakesh Malladi, Anand Dabak, Nitish Krishna Murthy

Proceedings Volume 9063, 90630Q (2014) https://doi.org/10.1117/12.2044613

KEYWORDS: Waveguides, Mathematical modeling, Transducers, Signal attenuation, Modeling, Ultrasonography, Wave propagation, Ultrasonics, Wave plates, Structural health monitoring

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Structural Health monitoring refers to monitoring the health of plate-like walls of large reactors, pipelines and other structures in terms of corrosion detection and thickness estimation. The objective of this work is modeling the ultrasonic guided waves generated in a plate. The piezoelectric is excited by an input pulse to generate ultrasonic guided lamb waves in the plate that are received by another piezoelectric transducer. In contrast with existing methods, we develop a mathematical model of the direct component of the signal (DCS) recorded at the terminals of the piezoelectric transducer. The DCS model uses maximum likelihood technique to estimate the different parameters, namely the time delay of the signal due to the transducer delay and amplitude scaling of all the lamb wave modes due to attenuation, while taking into account the received signal spreading in time due to dispersion. The maximum likelihood estimate minimizes the energy difference between the experimental and the DCS model-generated signal. We demonstrate that the DCS model matches closely with experimentally recorded signals and show it can be used to estimate thickness of the plate. The main idea of the thickness estimation algorithm is to generate a bank of DCS model-generated signals, each corresponding to a different thickness of the plate and then find the closest match among these signals to the received signal, resulting in an estimate of the thickness of the plate. Therefore our approach provides a complementary suite of analytics to the existing thickness monitoring approaches.

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