158 related articles for article (PubMed ID: 38381738)
1. An adaptive metaheuristic optimization approach for Tennessee Eastman process for an industrial fault tolerant control system.
Mustafa FE; Ahmed I; Basit A; Alqahtani M; Khalid M
PLoS One; 2024; 19(2):e0296471. PubMed ID: 38381738
[TBL] [Abstract][Full Text] [Related]
2. An improved approach for fault detection by simultaneous overcoming of high-dimensionality, autocorrelation, and time-variability.
Hajarian N; Movahedi Sobhani F; Sadjadi SJ
PLoS One; 2020; 15(12):e0243146. PubMed ID: 33332390
[TBL] [Abstract][Full Text] [Related]
3. Toward Robust Fault Identification of Complex Industrial Processes Using Stacked Sparse-Denoising Autoencoder With Softmax Classifier.
Liu J; Xu L; Xie Y; Ma T; Wang J; Tang Z; Gui W; Yin H; Jahanshahi H
IEEE Trans Cybern; 2023 Jan; 53(1):428-442. PubMed ID: 34550897
[TBL] [Abstract][Full Text] [Related]
4. Simultaneous Fault Detection and Identification in Continuous Processes via nonlinear Support Vector Machine based Feature Selection.
Onel M; Kieslich CA; Guzman YA; Pistikopoulos EN
Int Symp Process Syst Eng; 2018; 44():2077-2082. PubMed ID: 30534633
[TBL] [Abstract][Full Text] [Related]
5. A Fault Detection Method Based on CPSO-Improved KICA.
Liu M; Li X; Lou C; Jiang J
Entropy (Basel); 2019 Jul; 21(7):. PubMed ID: 33267382
[TBL] [Abstract][Full Text] [Related]
6. Adaptive PCA based fault diagnosis scheme in imperial smelting process.
Hu Z; Chen Z; Gui W; Jiang B
ISA Trans; 2014 Sep; 53(5):1446-55. PubMed ID: 24439836
[TBL] [Abstract][Full Text] [Related]
7. Fault Diagnosis of Tennessee-Eastman Process Using Orthogonal Incremental Extreme Learning Machine Based on Driving Amount.
Zou W; Xia Y; Li H
IEEE Trans Cybern; 2018 Dec; 48(12):3403-3410. PubMed ID: 29994325
[TBL] [Abstract][Full Text] [Related]
8. Contrastive Learning for Fault Detection and Diagnostics in the Context of Changing Operating Conditions and Novel Fault Types.
Rombach K; Michau G; Fink O
Sensors (Basel); 2021 May; 21(10):. PubMed ID: 34065164
[TBL] [Abstract][Full Text] [Related]
9. A Nonlinear Support Vector Machine-Based Feature Selection Approach for Fault Detection and Diagnosis: Application to the Tennessee Eastman Process.
Onel M; Kieslich CA; Pistikopoulos EN
AIChE J; 2019 Mar; 65(3):992-1005. PubMed ID: 32377021
[TBL] [Abstract][Full Text] [Related]
10. A Fault Prediction and Cause Identification Approach in Complex Industrial Processes Based on Deep Learning.
Li Y
Comput Intell Neurosci; 2021; 2021():6612342. PubMed ID: 33747072
[TBL] [Abstract][Full Text] [Related]
11. Optimal sensor location design for reliable fault detection in presence of false alarms.
Yang F; Xiao D; Shah SL
Sensors (Basel); 2009; 9(11):8579-92. PubMed ID: 22291524
[TBL] [Abstract][Full Text] [Related]
12. Deep Subdomain Learning Adaptation Network: A Sensor Fault-Tolerant Soft Sensor for Industrial Processes.
Zhang X; Song C; Zhao J; Xu Z; Deng X
IEEE Trans Neural Netw Learn Syst; 2022 Dec; PP():. PubMed ID: 37015656
[TBL] [Abstract][Full Text] [Related]
13. A new elite opposite sparrow search algorithm-based optimized LightGBM approach for fault diagnosis.
Fang Q; Shen B; Xue J
J Ambient Intell Humaniz Comput; 2022 Jan; ():1-19. PubMed ID: 35096192
[TBL] [Abstract][Full Text] [Related]
14. A latent feature oriented dictionary learning method for closed-loop process monitoring.
Huang K; Zhang L; Sun B; Liang X; Yang C; Gui W
ISA Trans; 2022 Dec; 131():552-565. PubMed ID: 35537874
[TBL] [Abstract][Full Text] [Related]
15. Reducing false alarm rates for critical arrhythmias using the arterial blood pressure waveform.
Aboukhalil A; Nielsen L; Saeed M; Mark RG; Clifford GD
J Biomed Inform; 2008 Jun; 41(3):442-51. PubMed ID: 18440873
[TBL] [Abstract][Full Text] [Related]
16. Artificial Intelligence Technologies for Coping with Alarm Fatigue in Hospital Environments Because of Sensory Overload: Algorithm Development and Validation.
Fernandes CO; Miles S; Lucena CJP; Cowan D
J Med Internet Res; 2019 Nov; 21(11):e15406. PubMed ID: 31769762
[TBL] [Abstract][Full Text] [Related]
17. Fault Detection of Wind Turbine Gearboxes Based on IBOA-ERF.
Tang M; Cao C; Wu H; Zhu H; Tang J; Peng Z; Wang Y
Sensors (Basel); 2022 Sep; 22(18):. PubMed ID: 36146174
[TBL] [Abstract][Full Text] [Related]
18. Fault Detection and Diagnosis in Industrial Processes with Variational Autoencoder: A Comprehensive Study.
Zhu J; Jiang M; Liu Z
Sensors (Basel); 2021 Dec; 22(1):. PubMed ID: 35009769
[TBL] [Abstract][Full Text] [Related]
19. Performance evaluation of fault detection methods for wastewater treatment processes.
Corominas L; Villez K; Aguado D; Rieger L; Rosén C; Vanrolleghem PA
Biotechnol Bioeng; 2011 Feb; 108(2):333-44. PubMed ID: 20882518
[TBL] [Abstract][Full Text] [Related]
20. Incremental Variational Bayesian Gaussian Mixture Model With Decremental Optimization for Distribution Accommodation and Fine-Scale Adaptive Process Monitoring.
Dai Q; Zhao C; Huang B
IEEE Trans Cybern; 2023 Aug; 53(8):5094-5107. PubMed ID: 35666782
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]