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http://dx.doi.org/10.20466/KPVP.2017.13.1.040

Study on the Extraction of Nuclear Power Plant Failure Patterns using AAKR  

Park, Kibeom ((주)엠앤디)
Ahn, Hongmin ((주)엠앤디)
Kang, Seongki ((주)엠앤디)
Chai, Jangbom (아주대학교 기계공학부)
Publication Information
Transactions of the Korean Society of Pressure Vessels and Piping / v.13, no.1, 2017 , pp. 40-47 More about this Journal
Abstract
In this paper, we investigate the feasibility of a strategy of failure detection and identification. The point of proposed strategy includes a pattern extraction approach for failure identification using Auto-Associative Kernel Regression (AAKR). We consider a simulation data concerning 605 signals of a Generic Pressurized Water Reactor(GPWR). In the application, the reconstructions are provided by a set of AAKR models, whose input signals have been selected by Correlation Analysis(CA) for the identification of the groups. The failure pattern is extracted by analyzing the residuals of observations and reconstructions. We present the possibility of extraction of patterns for six failure.
Keywords
Simulator; Auto-Associative Kernel Regression(AAKR); Correlation Analysis; Pattern Extraction;
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