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Detecting Abrupt Leaks in Blended Underground Storage Tanks
Authors:Ryan S. Gill  Michael I. Baron
Affiliation:1. Department of Mathematics , University of Louisville , Louisville , Kentucky , USA;2. Programs in Mathematical Sciences , University of Texas at Dallas , Dallas , Texas , USA
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.
Keywords:Multiple change points  Blended underground storage tank leak model  Least squares estimation  Confidence estimation
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