Nonlinear partial least square (NPLS) methods with generalized likelihood ratio test (GLRT) for fault detection and diagnosis of chemical processes

Chiranjivi Botre, Majdi Mansouri, Mohamed Nounou, Hazem Nounou, M. Nazmul Karim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish
Title of host publicationFuels and Petrochemicals Division 2016 - Core Programming Area at the 2016 AIChE Spring Meeting and 12th Global Congress on Process Safety
PublisherAIChE
Pages201-215
Number of pages15
ISBN (Electronic)9781510824942
Publication statusPublished - 2016
EventFuels and Petrochemicals Division 2016 - Core Programming Area at the 2016 AIChE Spring Meeting and 12th Global Congress on Process Safety - Houston, United States
Duration: 10 Apr 201614 Apr 2016

Other

OtherFuels and Petrochemicals Division 2016 - Core Programming Area at the 2016 AIChE Spring Meeting and 12th Global Congress on Process Safety
CountryUnited States
CityHouston
Period10/4/1614/4/16

Fingerprint

Fault detection
Failure analysis
Neural networks

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • Safety, Risk, Reliability and Quality
  • Fuel Technology

Cite this

Botre, C., Mansouri, M., Nounou, M., Nounou, H., & Karim, M. N. (2016). Nonlinear partial least square (NPLS) methods with generalized likelihood ratio test (GLRT) for fault detection and diagnosis of chemical processes. In Fuels and Petrochemicals Division 2016 - Core Programming Area at the 2016 AIChE Spring Meeting and 12th Global Congress on Process Safety (pp. 201-215). AIChE.

Nonlinear partial least square (NPLS) methods with generalized likelihood ratio test (GLRT) for fault detection and diagnosis of chemical processes. / Botre, Chiranjivi; Mansouri, Majdi; Nounou, Mohamed; Nounou, Hazem; Karim, M. Nazmul.

Fuels and Petrochemicals Division 2016 - Core Programming Area at the 2016 AIChE Spring Meeting and 12th Global Congress on Process Safety. AIChE, 2016. p. 201-215.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Botre, C, Mansouri, M, Nounou, M, Nounou, H & Karim, MN 2016, Nonlinear partial least square (NPLS) methods with generalized likelihood ratio test (GLRT) for fault detection and diagnosis of chemical processes. in Fuels and Petrochemicals Division 2016 - Core Programming Area at the 2016 AIChE Spring Meeting and 12th Global Congress on Process Safety. AIChE, pp. 201-215, Fuels and Petrochemicals Division 2016 - Core Programming Area at the 2016 AIChE Spring Meeting and 12th Global Congress on Process Safety, Houston, United States, 10/4/16.
Botre C, Mansouri M, Nounou M, Nounou H, Karim MN. Nonlinear partial least square (NPLS) methods with generalized likelihood ratio test (GLRT) for fault detection and diagnosis of chemical processes. In Fuels and Petrochemicals Division 2016 - Core Programming Area at the 2016 AIChE Spring Meeting and 12th Global Congress on Process Safety. AIChE. 2016. p. 201-215
Botre, Chiranjivi ; Mansouri, Majdi ; Nounou, Mohamed ; Nounou, Hazem ; Karim, M. Nazmul. / Nonlinear partial least square (NPLS) methods with generalized likelihood ratio test (GLRT) for fault detection and diagnosis of chemical processes. Fuels and Petrochemicals Division 2016 - Core Programming Area at the 2016 AIChE Spring Meeting and 12th Global Congress on Process Safety. AIChE, 2016. pp. 201-215
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