Dunia, Ricardo, Edgar, Thomas F., Nixon, Mark (2013) Process monitoring using principal components in parallel coordinates. AIChE Journal, 59 (2). 445-456 doi:10.1002/aic.13846

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Reference Type	Journal (article/letter/editorial)
Title	Process monitoring using principal components in parallel coordinates
Journal	AIChE Journal
Authors	Dunia, Ricardo		Author
	Edgar, Thomas F.		Author
	Nixon, Mark		Author
Year	2013 (February)	Volume	59
Issue	2
Publisher	Wiley
DOI	doi:10.1002/aic.13846Search in ResearchGate
	Generate Citation Formats
Mindat Ref. ID	6285735	Long-form Identifier	mindat:1:5:6285735:8
GUID	0
Full Reference	Dunia, Ricardo, Edgar, Thomas F., Nixon, Mark (2013) Process monitoring using principal components in parallel coordinates. AIChE Journal, 59 (2). 445-456 doi:10.1002/aic.13846
Plain Text	Dunia, Ricardo, Edgar, Thomas F., Nixon, Mark (2013) Process monitoring using principal components in parallel coordinates. AIChE Journal, 59 (2). 445-456 doi:10.1002/aic.13846
In	(2013, February) AIChE Journal Vol. 59 (2) Wiley

	Wang, Ray C., Edgar, Thomas F., Baldea, Michael, Nixon, Mark, Wojsznis, Willy, Dunia, Ricardo (2015) Process fault detection using time-explicit Kiviat diagrams. AIChE Journal, 61 (12). 4277-4293 doi:10.1002/aic.15054
	Dunia, Ricardo, Qin, S. Joe, Edgar, Thomas F., McAvoy, Thomas J. (1996) Identification of faulty sensors using principal component analysis. AIChE Journal, 42 (10). 2797-2812 doi:10.1002/aic.690421011
	Dunia, Ricardo, Rochelle, Gary, Edgar, Thomas F., Nixon, Mark (2014) Multivariate monitoring of a carbon dioxide removal process. Computers & Chemical Engineering, 60. 381-395 doi:10.1016/j.compchemeng.2013.09.010
	Xu, Shu, Baldea, Michael, Edgar, Thomas F., Wojsznis, Willy, Blevins, Terrence, Nixon, Mark (2015) An improved methodology for outlier detection in dynamic datasets. AIChE Journal, 61 (2). 419-433 doi:10.1002/aic.14631
	Dunia, Ricardo, Joe Qin, S., Edgar, Thomas F., McAvoy, Thomas J. (1996) Use of principal component analysis for sensor fault identification. Computers & Chemical Engineering, 20. doi:10.1016/0098-1354(96)00128-7
	*Nomikos, Paul, MacGregor, John F. (1994) Monitoring batch processes using multiway principal component analysis. AIChE Journal, 40 (8). 1361-1375 doi:10.1002/aic.690400809*
	*Kramer, Mark A. (1991) Nonlinear principal component analysis using autoassociative neural networks. AIChE Journal, 37 (2). 233-243 doi:10.1002/aic.690370209*
	*Yan, Lingqing, Edgar, Thomas F., Baldea, Michael (2021) Dynamic process intensification: Fundamentals and implementation to ternary distillation. AIChE Journal, 67 (8) doi:10.1002/aic.17262*
	*Yoon, Seongkyu, MacGregor, John F. (2004) Principal-component analysis of multiscale data for process monitoring and fault diagnosis. AIChE Journal, 50 (11). 2891-2903 doi:10.1002/aic.10260*
	*Qin, S. Joe, Zheng, Yingying (2013) Quality-relevant and process-relevant fault monitoring with concurrent projection to latent structures. AIChE Journal, 59 (2). 496-504 doi:10.1002/aic.13959*
	*Ge, Zhiqiang, Song, Zhihuan (2013) Bayesian inference and joint probability analysis for batch process monitoring. AIChE Journal, 59 (10). 3702-3713 doi:10.1002/aic.14119*

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Dunia, Ricardo, Edgar, Thomas F., Nixon, Mark (2013) Process monitoring using principal components in parallel coordinates. AIChE Journal, 59 (2). 445-456 doi:10.1002/aic.13846

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