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Proceedings Paper

Modelling ultrasound guided wave propagation for plate thickness measurement
Author(s): Rakesh Malladi; Anand Dabak; Nitish Krishna Murthy
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Paper Abstract

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.

Paper Details

Date Published: 9 March 2014
PDF: 10 pages
Proc. SPIE 9063, Nondestructive Characterization for Composite Materials, Aerospace Engineering, Civil Infrastructure, and Homeland Security 2014, 90630Q (9 March 2014); doi: 10.1117/12.2044613
Show Author Affiliations
Rakesh Malladi, Rice Univ. (United States)
Anand Dabak, Texas Instruments Inc. (United States)
Nitish Krishna Murthy, Texas Instruments Inc. (United States)

Published in SPIE Proceedings Vol. 9063:
Nondestructive Characterization for Composite Materials, Aerospace Engineering, Civil Infrastructure, and Homeland Security 2014
H. Felix Wu; Tzu-Yang Yu; Andrew L. Gyekenyesi; Peter J. Shull, Editor(s)

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