Original paper
Improved PCA method for sensor fault detection and isolation in a nuclear power plant
Abstract
An improved principal component analysis (PCA) method is applied for sensor fault detection and isolation (FDI) in a nuclear power plant (NPP) in this paper. Data pre-processing and false alarm reducing methods are combined with general PCA method to improve the model performance in practice. In data pre-processing, singular points and random fluctuations in the original data are eliminated with various techniques respectively. In fault...
Paper Details
Title
Improved PCA method for sensor fault detection and isolation in a nuclear power plant
Published Date
Feb 1, 2019
Volume
51
Issue
1
Pages
146 - 154
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