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‘Statistical methods for automatic crack detection based on vibrothermography sequence‐of‐images data’ by M. Li, S. D. Holland and W. Q. Meeker: Rejoinder

‘Statistical methods for automatic crack detection based on vibrothermography sequence‐of‐images... We would like to thank Professors Volf and Guerin for taking the time to carefully read our paper and prepare the thought‐provoking discussions. Professor Volf raises an important question about robustness of the matched‐filter method when the crack signature is not correctly specified. Of course this is important because the crack signature is never specified exactly; different cracks can have different spatial shapes. Although the Gaussian shape provides a good agreement to most of the crack signals that we have seen, some cracks provide a signal with two peaks, one at each of the crack tips. We conducted some simple experiments, especially with respect to the spatial shape, while writing our paper and came to the same conclusion as Professor Volf. We believe that most of the value of the matched filter in this application comes from the strong and consistent temporal pattern shown on the left‐hand side of Figure 3 of our paper. This pattern can be expected to be consistent across various crack morphologies. Thus, the performance of the matched filter could be expected to be robust to misspecification of the spatial pattern. It would, however, be interesting to extend Professor Volf's sensitivity study to three http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Applied Stochastic Models in Business and Industry Wiley

‘Statistical methods for automatic crack detection based on vibrothermography sequence‐of‐images data’ by M. Li, S. D. Holland and W. Q. Meeker: Rejoinder

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References (1)

Publisher
Wiley
Copyright
Copyright © 2010 John Wiley & Sons, Ltd.
ISSN
1524-1904
eISSN
1526-4025
DOI
10.1002/asmb.867
Publisher site
See Article on Publisher Site

Abstract

We would like to thank Professors Volf and Guerin for taking the time to carefully read our paper and prepare the thought‐provoking discussions. Professor Volf raises an important question about robustness of the matched‐filter method when the crack signature is not correctly specified. Of course this is important because the crack signature is never specified exactly; different cracks can have different spatial shapes. Although the Gaussian shape provides a good agreement to most of the crack signals that we have seen, some cracks provide a signal with two peaks, one at each of the crack tips. We conducted some simple experiments, especially with respect to the spatial shape, while writing our paper and came to the same conclusion as Professor Volf. We believe that most of the value of the matched filter in this application comes from the strong and consistent temporal pattern shown on the left‐hand side of Figure 3 of our paper. This pattern can be expected to be consistent across various crack morphologies. Thus, the performance of the matched filter could be expected to be robust to misspecification of the spatial pattern. It would, however, be interesting to extend Professor Volf's sensitivity study to three

Journal

Applied Stochastic Models in Business and IndustryWiley

Published: Sep 1, 2010

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