Detecting Abrupt Leaks in Blended Underground Storage Tanks |
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Authors: | Ryan S. Gill Michael I. Baron |
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Affiliation: | 1. Department of Mathematics , University of Louisville , Louisville , Kentucky , USA;2. Programs in Mathematical Sciences , University of Texas at Dallas , Dallas , Texas , USA |
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Abstract: | We suggest and compare two multiple change-point algorithms (segmentation and sequential) for accurate detection of the onset of abrupt leaks in blended underground storage tanks. We apply these algorithms to two simulated scenarios to demonstrate the advantages of the sequential algorithm, and then we apply the sequential algorithm to the Cary blended site data. In addition, we obtain a confidence set for the locations of the change points conditional on the number of change points by inverting the related hypothesis test. |
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Keywords: | Multiple change points Blended underground storage tank leak model Least squares estimation Confidence estimation |
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