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ECOLE SUPÉRIEURE D'ÉLECTRICITÉ Une grande école d'ingénieurs au cœur des sciences de l'information,de l'énergie et des systèmes |
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Conference papers
A modified Auto Associative Kernel Regression method for robust signal reconstruction in nuclear power plant components
Abstract : The application of the Auto Associative Kernel Regression (AAKR) method to the reconstruction of correlat-ed plant signals is not satisfactory from the point of view of the robustness, i.e. the capability of reconstruct-ing abnormal signals to the values expected in normal conditions. To overtake this limitation, we propose to modify the traditional AAKR method by defining a novel measure of the similarity between the current measurement and the historical patterns. An application of the proposed modified AAKR method to the con-dition monitoring of a pressurizer of a Pressurized Water Reactor (PWR) Nuclear Power Plant (NPP) shows benefits with respect to the traditional AAKR method, in terms of earlier detection of abnormal conditions and correct identification of the signals responsible for triggering the detection.
Keywords :
Signal Reconstruction
Fault Detection
Cited literature [14 references]
https://hal-supelec.archives-ouvertes.fr/hal-01262146
Contributor : Pietro Turati Connect in order to contact the contributor
Submitted on : Tuesday, January 26, 2016 - 12:20:23 PM
Last modification on : Saturday, May 8, 2021 - 3:26:55 AM
Contributor : Pietro Turati Connect in order to contact the contributor
Submitted on : Tuesday, January 26, 2016 - 12:20:23 PM
Last modification on : Saturday, May 8, 2021 - 3:26:55 AM
Annex
2014_ESREL_A modified Auto Ass...
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