1 |
YIN S, DING S X, XIE X, et al. A review on basic data-driven approaches for industrial process monitoring[J]. IEEE Transactions on Industrial Electronics, 2014, 61(11): 6418-6428.
|
2 |
GE Z. Review on data-driven modeling and monitoring for plant-wide industrial processes[J]. Chemometrics and Intelligent Laboratory Systems, 2017, 171: 16-25.
|
3 |
TIDRIRI K, CHATTI N, VERRON S, et al. Bridging data-driven and model-based approaches for process fault diagnosis and health monitoring: a review of researches and future challenges[J]. Annual Reviews in Control, 2016, 42: 63-81.
|
4 |
TONG C, LAN T, YU H, et al. Distributed partial least squares based residual generation for statistical process monitoring[J]. Journal of Process Control, 2019, 75:77-85.
|
5 |
马方圆, 林德溪, 许明阳, 等. 基于多元统计方法的过程单元缓变故障识别[J]. 化工进展, 2020, 39(4): 1267-1272.
|
|
MA Fangyuan, LIN Dexi, XU Mingyang, et al. Early identification of small shift in process unit based on multivariate statistical method[J]. Chemical Industry and Engineering Progress, 2020, 39(4): 1267-1272.
|
6 |
LAN T, TONG C, YU H, et al. Nonlinear process monitoring based on decentralized generalized regression neural networks[J]. Expert Systems with Applications, 2020, 150: 113273.
|
7 |
SANCHEZ-FERNANDEZ A, BALDAN F J, SAINZ-PALMERO G I, et al. Fault detection based on time series modeling and multivariate statistical process control[J]. Chemometrics and Intelligent Laboratory Systems, 2018, 182: 57-69.
|
8 |
PENG X, DING S X, DU W, et al. Distributed process monitoring based on canonical correlation analysis with partly-connected topology[J]. Control Engineering Practice, 2020, 101: 104500.
|
9 |
LI W, LI H, GU S, et al. Process fault diagnosis with model-and knowledge-based approaches: advances and opportunities[J]. Control Engineering Practice, 2020, 105: 104637.
|
10 |
YIM S Y, ANANTHAKUMAR H G, BENABBAS L, et al. Using process topology in plant-wide control loop performance assessment[J]. Computers & Chemical Engineering, 2006, 31(2): 86-99.
|
11 |
JIANG H, PATAARDHAN R, SHAH S L. Root cause diagnosis of plant-wide oscillations using the concept of adjacency matrix[J]. Journal of Process Control, 2009, 19(8): 1347-1354.
|
12 |
LINDNER B, AURET L. Data-driven fault detection with process topology for fault identification[J]. IFAC Proceedings Volumes, 2014, 47(3):8903-8908.
|
13 |
LINDNER B, AURET L. Application of data-based process topology and feature extraction for fault diagnosis of an industrial platinum group metals concentrator plant [J]. IFAC—PapersOnLine, 2015, 48(17): 102-107.
|
14 |
MONTGOMERY DOUGLAS C.. Introduction to statistical quality control 7th edition [J]. Technometrics, 2012, 49(1):108-109.
|
15 |
QIN S J. Survey on data-driven industrial process monitoring and diagnosis [J]. Annual Reviews in Control, 2012, 36(2): 220-234.
|
16 |
YEN J Y. Finding the K shortest loopless paths in a network[J]. Management Science, 1971, 17(11):712-716.
|