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Title Fault detection and isolation using correspondence analysis
 
Names DETROJA, KP (author)
GUDI, RD (author)
PATWARDHAN, SC (author)
ROY, K (author)
Date Issued 2006 (iso8601)
Abstract In this paper, a new approach to fault detection and diagnosis that is based on correspondence analysis (CA) is proposed. CA is a powerful multivariate technique based on the generalized singular value decomposition. The merits of using CA lie in its ability to depict rows as well as columns as points in the dual lower dimensional vector space. CA has been shown to capture association between various features and events quite effectively. The key strengths of CA, for fault detection and diagnosis, are validated on data involving simulations as well as experimental data obtained from a laboratory-scale setup.
Genre Article; Proceedings Paper
Topic principal component analysis
Identifier 0888-5885
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