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Kalman filtering techniques for fault detection and diagnosis in continuously stirred tank reactor (Cstr)

Publication Type : Journal Article

Publisher : International Journal of Applied Engineering Research

Source : International Journal of Applied Engineering Research, Volume 10, Number 17, p.37346-37350 (2015)

Url : https://www.scopus.com/inward/record.uri?eid=2-s2.0-84942617553&partnerID=40&md5=e6d1c7848c44bd4fbc2ea71b4a4350c8

Keywords : continuously stirred tank reactor, Fault detection, in MATLAB, techniques

Campus : Coimbatore

School : School of Engineering

Department : Electronics and Communication

Year : 2015

Abstract : Fault detection and isolation is one of the major challenges every chemical industry is concerned with, because it deals with the performance of the machinery. Fault detection methods play an essential role in reducing costs, increasing safety and minimizing the effect on the surroundings[1]. To study and compare various Fault detection and isolation techniques, the mathematical model of a continuously stirred tank reactor (CSTR) is implemented in MATLAB. The output, which is obtained from this model, is fed to Kalman filter, which in turn gives a residue that is used to detect the faults present in the system. The difference between the measured process variables and their estimate is called a residue[2]. The same method is used for detecting faults for non-linear state equations with Extended Kalman filter and the residue is obtained from the same. From the residues obtained from Kalman and Extended Kalman filter a conclusion is made that the Extended Kalman filter gives more accurate results. © Research India Publications.

Cite this Research Publication : P. V. Sunil Nag, Nair, S. R. P., Gowtham, M., Sibichakravarthy, V., Shivendran, T. D., and Manjunath, S., “Kalman filtering techniques for fault detection and diagnosis in continuously stirred tank reactor (Cstr)”, International Journal of Applied Engineering Research, vol. 10, pp. 37346-37350, 2015.

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