@inproceedings{8c79a6865537435697fe2ea736cb33b0,
title = "Nonlinear partial least square (NPLS) methods with generalized likelihood ratio test (GLRT) for fault detection and diagnosis of chemical processes",
abstract = "We presented the problem of fault detection using kernel partial least square (PLS) -based generalized likelihood ratio test (GLRT) and neural net partial least square (PLS) -based GLRT. • TEP results demonstrate the effectiveness of the KPLS -based GLRT technique for detection of multiple faults with low false alarm rate and early fault detection • KPLS regression model is used to predict concentration of the product from online process variable.",
author = "Chiranjivi Botre and Majdi Mansouri and Nounou, \{Mohamed N.\} and Nounou, \{Hazem N.\} and Karim, \{M. Nazmul\}",
year = "2016",
language = "English",
series = "Fuels and Petrochemicals Division 2016 - Core Programming Area at the 2016 AIChE Spring Meeting and 12th Global Congress on Process Safety",
publisher = "AIChE",
pages = "201--215",
booktitle = "Fuels and Petrochemicals Division 2016 - Core Programming Area at the 2016 AIChE Spring Meeting and 12th Global Congress on Process Safety",
note = "Fuels and Petrochemicals Division 2016 - Core Programming Area at the 2016 AIChE Spring Meeting and 12th Global Congress on Process Safety ; Conference date: 10-04-2016 Through 14-04-2016",
}