Record Details

A possibilistic clustering approach to novel fault detection and isolation

DSpace at IIT Bombay

View Archive Info
 
 
Field Value
 
Title A possibilistic clustering approach to novel fault detection and isolation
 
Creator DETROJA, KP
GUDI, RD
PATWARDHAN, SC
 
Subject computer simulation
benchmarking
computer simulation
classification (of information)
probabilistic logics
 
Description In this paper, a new approach for fault detection and isolation that is based on the possibilistic clustering algorithm is proposed. Fault detection and isolation (FDI) is shown here to be a pattern classification problem, which can be solved using clustering and classification techniques. A possibilistic clustering based approach is proposed here to address some of the shortcomings of the fuzzy c-means (FCM) algorithm. The probabilistic constraint imposed on the membership value in the FCM algorithm is relaxed in the possibilistic clustering algorithm. Because of this relaxation, the possibilistic approach is shown in this paper to give more consistent results in the context of the FDI tasks. The possibilistic clustering approach has also been used to detect novel fault scenarios, for which the data was not available while training. Fault signatures that change as a function of the fault intensities are represented as fault lines, which have been shown to be useful to classify faults that can manifest with different intensities. The proposed approach has been validated here through simulations involving a benchmark quadruple tank process and also through experimental case studies on the same setup. For large scale systems, it is proposed to use the possibilistic clustering based approach in the lower dimensional approximations generated by algorithms such as PCA. Towards this end, finally, we also demonstrate the key merits of the algorithm for plant wide monitoring study using a simulation of the benchmark Tennessee Eastman problem.
 
Publisher Elsevier
 
Date 2009-03-05T08:23:35Z
2011-11-25T18:34:09Z
2011-12-26T13:06:58Z
2011-12-27T05:54:57Z
2009-03-05T08:23:35Z
2011-11-25T18:34:09Z
2011-12-26T13:06:58Z
2011-12-27T05:54:57Z
2006
 
Type Article
 
Identifier Journal of Process Control 16(10), 1055-1073
0959-1524
http://dx.doi.org/10.1016/j.jprocont.2006.07.001
http://hdl.handle.net/10054/871
http://dspace.library.iitb.ac.in/xmlui/handle/10054/871
 
Language en