TY  - JOUR
ID  - scholars12606
KW  - Accident prevention; Chemical industry; Error statistics; Fault detection; Monitoring; Optimization; Process control; Process monitoring; Wavelet transforms
KW  -  Chemical process systems; Continuous stirred tank reactor; Kernel principal component analyses (KPCA); Monitoring techniques; Multi-scale frameworks; Process disturbances; Real-time process monitoring; Squared prediction errors
KW  -  Real time systems
N2  - Process monitoring techniques are used in the chemical industry to improve both product quality and plant safety. In chemical process systems, real-time process monitoring is one of the most crucial and challenging tasks for efficient quality control of the final products and process optimization. The existing multiscale process monitoring techniques use offline decomposition tools that restrict their applications to real-time process monitoring. In this study, to improve the performance of monitoring real-time process data, we have combined moving window-based wavelet transform and kernel principal component analysis (KPCA). A case study is performed on a typical continuous stirred tank reactor system. Performance analysis (based on T2 and squared prediction error statistics and contribution plots) shows that the technique successfully detects and identifies process disturbances, sensor bias, and process faults. Moreover, a comparison with PCA and KPCA methods shows that the proposed approach provides a 100 fault detection rate for the step-change fault patterns and has considerably improved detection rates for the random and ramp-change fault patterns. © 2020 American Chemical Society
IS  - 41
VL  - 59
A1  - Maulud, A.S.
A1  - Nawaz, M.
A1  - Zabiri, H.
A1  - Suleman, H.
A1  - Tufa, L.D.
JF  - Industrial and Engineering Chemistry Research
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85096033121&doi=10.1021%2facs.iecr.0c02288&partnerID=40&md5=826402f230faa0d32700b43f35dbb54e
Y1  - 2020///
SP  - 18595
TI  - Multiscale framework for real-time process monitoring of nonlinear chemical process systems
N1  - cited By 15
AV  - none
EP  - 18606
PB  - American Chemical Society
SN  - 08885885
ER  -