Rényi Entropy Filter for Anomaly Detection with Eddy Current Remote Field Sensors

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dc.contributor.authorSheikhi, Farid
dc.contributor.authorSpinello, Davide
dc.contributor.authorGueaieb, Wail
dc.date.accessioned2015-09-09T16:31:20Z
dc.date.available2015-09-09T16:31:20Z
dc.date.created2015-06
dc.date.issued2015-06
dc.identifier.urihttp://hdl.handle.net/10393/32835
dc.identifier.urihttp://dx.doi.org/10.1109/JSEN.2015.2450236
dc.description.abstractWe consider a multi-channel remote field eddy current sensor apparatus, which is installed on a mobile robot deployed in pipelines with the mission of detecting defects. Features in raw sensory data that are associated with defects could be masked by noise and therefore difficult to identify in some instances. In order to enhance these features that potentially identify defects, we propose an entropy filter that maps raw sensory data points into a local entropy measure. In the entropy space, data are then classified by means of a thresholding procedure based on the Neyman–Pearson criterion. The effectiveness of the algorithm is demonstrated by applying it to different data sets obtained from field trials.
dc.description.sponsorshipNSERC, FedDev Ontario
dc.subjectEntropy
dc.subjectFiltering algorithms
dc.subjectRobot sensing systems
dc.subjectEddy currents
dc.subjectPipe inspection
dc.subjectFault detection
dc.titleRényi Entropy Filter for Anomaly Detection with Eddy Current Remote Field Sensors
dc.typeArticle
dc.identifier.doi10.1109/JSEN.2015.2450236
CollectionScience informatique et génie électrique - Publications // Electrical Engineering and Computer Science - Publications

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