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).
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页数：7
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