eprintid: 15962
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/59/62
datestamp: 2023-11-10 03:30:35
lastmod: 2023-11-10 03:30:35
status_changed: 2023-11-10 02:00:51
type: article
metadata_visibility: show
creators_name: Nawaz, M.
creators_name: Maulud, A.S.
creators_name: Zabiri, H.
creators_name: Taqvi, S.A.A.
creators_name: Idris, A.
title: Improved process monitoring using the CUSUM and EWMA-based multiscale PCA fault detection framework
ispublished: pub
keywords: Accident prevention; Chemical industry; Monitoring; Process control; Process monitoring, Comparative studies; Complex chemicals; Detection approach; Detection framework; Exponentially weighted moving average control charts; Monitoring techniques; Multi-scale principal component analysis; Square prediction errors, Fault detection
note: cited By 26
abstract: Process monitoring techniques are of paramount importance in the chemical industry to improve both the product quality and plant safety. Small or incipient irregularities may lead to severe degradation in complex chemical processes, and the conventional process monitoring techniques cannot detect these irregularities. In this study to improve the performance of monitoring, an online multiscale fault detection approach is proposed by integrating multiscale principal component analysis (MSPCA) with cumulative sum (CUSUM) and exponentially weighted moving average (EWMA) control charts. The new Hotelling's T2 and square prediction error (SPE) based fault detection indices are proposed to detect the incipient irregularities in the process data. The performance of the proposed fault detection methods was tested for simulated data obtained from the CSTR system and compared to that of conventional PCA and MSPCA based methods. The results demonstrate that the proposed EWMA based MSPCA fault detection method was successful in detecting the faults. Moreover, a comparative study shows that the SPE-EWMA monitoring index exhibits a better performance with lower values of missed detections ranging from 0 to 0.80 and false alarms ranging from 0 to 21.20. © 2020 The Chemical Industry and Engineering Society of China, and Chemical Industry Press
date: 2021
publisher: Materials China
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097665054&doi=10.1016%2fj.cjche.2020.08.035&partnerID=40&md5=4af3de63bb0dac758ecb5519eb1a0486
id_number: 10.1016/j.cjche.2020.08.035
full_text_status: none
publication: Chinese Journal of Chemical Engineering
volume: 29
pagerange: 253-265
refereed: TRUE
issn: 10049541
citation:   Nawaz, M. and Maulud, A.S. and Zabiri, H. and Taqvi, S.A.A. and Idris, A.  (2021) Improved process monitoring using the CUSUM and EWMA-based multiscale PCA fault detection framework.  Chinese Journal of Chemical Engineering, 29.  pp. 253-265.  ISSN 10049541