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Estimating Changes in SHM Performance Using Probability of Detection Degradation Functions

Jeffrey D. Kuhn1, Som R. Soni2

1 AFRL/RWME, Eglin AFB, Florida, USA
2 AFiT/ENV, Air Force Institute of Technology, Wright Patt AFB, OH, USA

Structural Longevity 2009, 2(1), 1-10. https://doi.org/10.3970/sl.2009.002.001

Abstract

Structural Health Monitoring (SHM) has been proposed by many researchers as a way to reduce maintenance cost and increase availability of aircraft fleets. But long term exposure to the aircraft environment can have a degrading effect on the performance of a given SHM system. Predictable performance of SHM systems after extended exposure to aircraft environmental factors is key to the effective implementation of SHM on aircraft fleets. This study shows how existing NDE reliability techniques can be extended to model changes in SHM system performance due to extended exposure to the aircraft environment. Degradation coef- ficients are added to the traditional probability of detection, POD(a), formulations described in MIL-HDBK-1823. A POD(a,n) surface is then derived to account for the effects of an environmental factor on SHM system performance. Example degradation coefficient values are derived using experimental results. Keywords: Structural Health Monitoring, Probability of Detection, S

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Cite This Article

APA Style
Kuhn, J.D., Soni, S.R. (2009). Estimating changes in SHM performance using probability of detection degradation functions. Structural Longevity, 2(1), 1-10. https://doi.org/10.3970/sl.2009.002.001
Vancouver Style
Kuhn JD, Soni SR. Estimating changes in SHM performance using probability of detection degradation functions. Structural Longevity . 2009;2(1):1-10 https://doi.org/10.3970/sl.2009.002.001
IEEE Style
J.D. Kuhn and S.R. Soni, “Estimating Changes in SHM Performance Using Probability of Detection Degradation Functions,” Structural Longevity , vol. 2, no. 1, pp. 1-10, 2009. https://doi.org/10.3970/sl.2009.002.001



cc Copyright © 2009 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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