Application of Possibilistic C-Means for Fault Detection in Nuclear Power Plant Data

被引：0

作者：

Perasso, Annalisa ^{[1
,2
]}

Campi, Cristina ^{[2
]}

Toraci, Cristian ^{[1
,3
]}

Benvenuto, Francesco ^{[4
]}

Piana, Michele ^{[1
,2
]}

Massone, Anna Maria ^{[2
]}

机构：

[1] Univ Genoa, Dipartimento Matemat, I-16146 Genoa, Italy

[2] CNR SPIN, I-16146 Genoa, Italy

[3] IRCCS San Martino IST, I-16146 Genoa, Italy

[4] Ansaldo Nucl SpA, I-16146 Genoa, Italy

来源：

JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER-TRANSACTIONS OF THE ASME | 2015年 / 137卷 / 06期

关键词：

D O I：

10.1115/1.4028809

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

This paper describes a classification method for automatic fault detection in nuclear power plant (NPP) data. The method takes as input time series associated to specific parameters and realizes signal classification by using a clustering algorithm based on possibilistic C-means (PCM). This approach is applied to time series recorded in a CANDU (R) power plant and is validated by comparison with results provided by a classification method based on principal component analysis (PCA).

引用

页数：7

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