Ultrasonic wave-based defect localization using probabilistic modeling

M. D. Todd*, E. B. Flynn, P. D. Wilcox, B. W. Drinkwater, A. J. Croxford, S. Kessler

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

5 Citations (Scopus)


This work presents a new approach rooted in maximum likelihood estimation for defect localization in sparse array guided wave ultrasonic interrogation applications. The approach constructs a minimally-informed statistical model of the guided wave process, where unknown or uncertain model parameters are assigned non-informative Bayesian prior distributions and integrated out of the a posteriori probability calculation. The premise of this localization approach is straightforward: the most likely defect location is the point on the structure with the maximum a posteriori probability of actually being the location of damage (i.e., the most probable location given a set of sensor measurements). The proposed approach is tested on a complex stiffened panel against other common localization approaches and found to have superior performance in all cases.

Original languageEnglish
Title of host publicationAIP Conference Proceedings
Number of pages8
Publication statusPublished - 13 Jul 2012
Event38th Annual Review of Progress in Quantitative Nondestructive Evaluation (QNDE 2011) - Burlington, VT, United States
Duration: 17 Jul 201122 Jul 2011
Conference number: 38


Conference38th Annual Review of Progress in Quantitative Nondestructive Evaluation (QNDE 2011)
Abbreviated titleQNDE 2011
Country/TerritoryUnited States
CityBurlington, VT


  • Bayesian Modeling
  • Sparse Array Localization
  • Ultrasonic Guided Waves


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