@article { ISI:000232838800009,
	title = {Knowledge incorporated support vector machines to detect faults in Tennessee Eastman Process},
	journal = {Computers \& Chemical Engineering},
	volume = {29},
	number = {10},
	year = {2005},
	month = {SEP},
	pages = {2128-2133},
	publisher = {PERGAMON-ELSEVIER SCIENCE LTD},
	type = {Article},
	address = {THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND},
	abstract = {<p>A support vector machine with knowledge incorporation is applied to detect the faults in Tennessee Eastman Process, a benchmark problem in chemical engineering. The knowledge incorporated algorithm takes advantage of the information on horizontal translation invariance in tangent direction of the instances in dataset. This essentially changes the representation of the input data while training the algorithm. These local translations do not alter the class membership of the instances in the dataset. The results on binary as well as multiple fault detection justify the use of knowledge incorporation. (c) 2005 Elsevier Ltd. All rights reserved.</p>},
	keywords = {fault detection, knowledge, support vector machines, Tennessee Eastman Process},
	issn = {0098-1354},
	doi = {10.1016/j.compchemeng.2005.06.006},
	author = {Kulkarni, A. and Jayaraman, Valadi K. and Kulkarni, B. D.}
}
@conference {44037,
	title = {Fault detection and analysis of Kapton film in fuel cells using image processing},
	booktitle = {International Conference on Computing, Analytics and Security Trends, CAST 2016},
	year = {2017},
	month = {28 April 2017},
	abstract = {<p>Fuel cell is one of the best alternatives of fossil energy in the modern scenario. But still there are some shortcomings such as durability and reliability, which block the wide application of fuel cells. To overcome these barriers, fault diagnosis is an efficient solution. This paper proposes a method for finding dimensional accuracies in Kapton films in membrane electrode assemblies (MEA) of fuel cells using image processing tools for offline fault analysis. {\textcopyright} 2016 IEEE.</p>},
	keywords = {Dimensional accuracy, Fault analysis, fault detection, Fossil energy, fuel cell, Gas fuel purification, image analysis, Image processing, Image processing tools, Kapton films, Membrane electrode assemblies, Offline, polyimides},
	isbn = {978-150901338-8},
	doi = {10.1109/CAST.2016.7915032},
	author = {Firdous, R. and Aherrao, S. and Narute, B. and Borkar, V.}
}
