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Anomaly detection in OECD Benchmark data using co-variance methods

Technical Report:

Abstract

OECD Benchmark data distributed for the SMORN VI Specialists Meeting in Reactor Noise were investigated for anomaly detection in artificially generated reactor noise benchmark analysis. It was observed that statistical features extracted from covariance matrix of frequency components are very sensitive in terms of the anomaly detection level. It is possible to create well defined alarm levels. (R.P.) 5 refs.; 23 figs.; 1 tab.
Authors:
Srinivasan, G S; [1]  Krinizs, K; [2]  Por, G [3] 
  1. Indira Gandhi Centre for Atomic Research, Kalpakkam (India)
  2. Hungarian Academy of Sciences, Budapest (Hungary). Central Research Inst. for Physics
  3. Budapesti Mueszaki Egyetem (Hungary). Inst. for Nuclear Techniques
Publication Date:
Feb 01, 1993
Product Type:
Technical Report
Report Number:
KFKI-1993-02/G
Reference Number:
SCA: 220100; PA: AIX-25:006516; EDB-94:012503; ERA-19:006650; NTS-94:015055; SN: 94001126468
Resource Relation:
Other Information: PBD: Feb 1993
Subject:
22 GENERAL STUDIES OF NUCLEAR REACTORS; REACTOR NOISE; BENCHMARKS; DATA COVARIANCES; EXPERIMENTAL DATA; STATISTICS; 220100; THEORY AND CALCULATION
OSTI ID:
10112981
Research Organizations:
Hungarian Academy of Sciences, Budapest (Hungary). Central Research Inst. for Physics
Country of Origin:
Hungary
Language:
English
Other Identifying Numbers:
Other: ON: DE94610775; TRN: HU9316203006516
Availability:
OSTI; NTIS (US Sales Only); INIS
Submitting Site:
INIS
Size:
29 p.
Announcement Date:
Jun 30, 2005

Technical Report:

Citation Formats

Srinivasan, G S, Krinizs, K, and Por, G. Anomaly detection in OECD Benchmark data using co-variance methods. Hungary: N. p., 1993. Web.
Srinivasan, G S, Krinizs, K, & Por, G. Anomaly detection in OECD Benchmark data using co-variance methods. Hungary.
Srinivasan, G S, Krinizs, K, and Por, G. 1993. "Anomaly detection in OECD Benchmark data using co-variance methods." Hungary.
@misc{etde_10112981,
title = {Anomaly detection in OECD Benchmark data using co-variance methods}
author = {Srinivasan, G S, Krinizs, K, and Por, G}
abstractNote = {OECD Benchmark data distributed for the SMORN VI Specialists Meeting in Reactor Noise were investigated for anomaly detection in artificially generated reactor noise benchmark analysis. It was observed that statistical features extracted from covariance matrix of frequency components are very sensitive in terms of the anomaly detection level. It is possible to create well defined alarm levels. (R.P.) 5 refs.; 23 figs.; 1 tab.}
place = {Hungary}
year = {1993}
month = {Feb}
}