A framework for data-driven fault detection and identification with multiscale kernel fisher discriminant analysis in chemical process systems / Norazwan Md Nor

A framework for data-driven fault detection and identification with multiscale kernel fisher discriminant analysis in chemical process systems / Norazwan Md Nor

Fault detection and identification (FDI) framework plays an important role to ensure consistent and reliable operation of chemical process systems. The FDI framework has two main tasks, namely to detect the presence of a fault and to classify the location and type of the fault. In most cases, it...

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Bibliographic Details
Main Author: Norazwan , Md Nor
Format: Thesis
Published: 2018
Subjects:
TP Chemical technology
Online Access:http://studentsrepo.um.edu.my/9357/
http://studentsrepo.um.edu.my/9357/1/Norazwan_Md_Nor.pdf
http://studentsrepo.um.edu.my/9357/6/norazwan.pdf

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