| 1 |
Oscillation detection in process industries - Part I: Review of the detection methods
Dambros JWV, Trierweiler JO, Farenzena M
Journal of Process Control, 78, 108, 2019 |
| 2 |
Oscillation detection in process industries - Part II: Industrial application
Dambros JWV, Trierweiler JO, Farenzena M, Kempf A, Longhi LGS, Teixeira HCG
Journal of Process Control, 78, 139, 2019 |
| 3 |
Performance monitoring of MIMO control system using Kullback-Leibler divergence
Wu P
Canadian Journal of Chemical Engineering, 96(7), 1559, 2018 |
| 4 |
Review and comparison of techniques of analysis of valve stiction: From modeling to smart diagnosis
di Capaci RB, Scali C
Chemical Engineering Research & Design, 130, 230, 2018 |
| 5 |
Searching historical data segments for process identification in feedback control loops
Wang JD, Su JJ, Zhao Y, Zhou DH
Computers & Chemical Engineering, 112, 6, 2018 |
| 6 |
Data Mining and Control Loop Performance Assessment: The Multivariate Case
Das L, Rengaswamy R, Srinivasan B
AIChE Journal, 63(8), 3311, 2017 |
| 7 |
PROCESS CONTROL PERFORMANCE EVALUATION IN THE CASE OF VARIABLE SET-POINT WITH EXPERIMENTAL APPLICATIONS
di Capaci RB, Scali C
Canadian Journal of Chemical Engineering, 95(9), 1707, 2017 |
| 8 |
A Novel Framework for Integrating Data Mining with Control Loop Performance Assessment
Das L, Srinivasan B, Rengaswamy R
AIChE Journal, 62(1), 146, 2016 |
| 9 |
A review of control loop monitoring and diagnosis: Prospects of controller maintenance in big data era
Gao XQ, Yang F, Shang C, Huang DX
Chinese Journal of Chemical Engineering, 24(8), 952, 2016 |
| 10 |
The current state of control loop performance monitoring - A survey of application in industry
Bauer M, Horch A, Xie L, Jelali M, Thornhill N
Journal of Process Control, 38, 1, 2016 |
