Fault Detection and Classification for Nonlinear Chemical Processes using Lasso and Gaussian Process

Industrial & Engineering Chemistry Research ◽

10.1021/acs.iecr.8b01110 ◽

2018 ◽

Vol 57 (27) ◽

pp. 8962-8977 ◽

Author(s):

Yuncheng Du ◽

Hector Budman ◽

Thomas A. Duever ◽

Dongping Du

Keyword(s):

Fault Detection ◽

Gaussian Process ◽

Chemical Processes ◽

Fault Detection And Classification

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Reduced Gaussian process regression for fault detection of chemical processes

2019 International Conference on Internet of Things, Embedded Systems and Communications (IINTEC) ◽

10.1109/iintec48298.2019.9112136 ◽

2019 ◽

Author(s):

Radhia Fezai ◽

Majdi Mansouri ◽

Nasreddine Bouguila ◽

Hazem Nounou ◽

Mohamed Nounou

Keyword(s):

Fault Detection ◽

Gaussian Process ◽

Gaussian Process Regression ◽

Chemical Processes

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A support vector clustering-based probabilistic method for unsupervised fault detection and classification of complex chemical processes using unlabeled data

AIChE Journal ◽

10.1002/aic.13816 ◽

2012 ◽

Vol 59 (2) ◽

pp. 407-419 ◽

Author(s):

Jie Yu

Keyword(s):

Fault Detection ◽

Probabilistic Method ◽

Chemical Processes ◽

Unlabeled Data ◽

Support Vector ◽

Complex Chemical ◽

Support Vector Clustering ◽

Fault Detection And Classification ◽

Vector Clustering

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Comparison of stochastic fault detection and classification algorithms for nonlinear chemical processes

Computers & Chemical Engineering ◽

10.1016/j.compchemeng.2017.05.016 ◽

2017 ◽

Vol 106 ◽

pp. 57-70 ◽

Author(s):

Yuncheng Du ◽

Hector Budman ◽

Thomas A. Duever

Keyword(s):

Fault Detection ◽

Chemical Processes ◽

Classification Algorithms ◽

Fault Detection And Classification

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Fault detection and classification in chemical processes using NMFSC and structural SVMs

The Canadian Journal of Chemical Engineering ◽

10.1002/cjce.21945 ◽

2013 ◽

Vol 92 (6) ◽

pp. 1016-1023 ◽

Author(s):

Yi Peng ◽

Xiaogang Chen ◽

Qixiang Ye ◽

Jianbin Jiao

Keyword(s):

Fault Detection ◽

Chemical Processes ◽

Fault Detection And Classification

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Fault detection and classification in chemical processes based on neural networks with feature extraction

ISA Transactions ◽

10.1016/s0019-0578(07)60013-5 ◽

2003 ◽

Vol 42 (4) ◽

pp. 651-664 ◽

Author(s):

Yifeng Zhou ◽

Juergen Hahn ◽

M. Sam Mannan

Keyword(s):

Neural Networks ◽

Feature Extraction ◽

Fault Detection ◽

Chemical Processes ◽

Fault Detection And Classification

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Deep Compression of Neural Networks for Fault Detection on Tennessee Eastman Chemical Processes

2021 IEEE 2nd International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering (ICBAIE) ◽

10.1109/icbaie52039.2021.9389826 ◽

2021 ◽

Author(s):

Mingxuan Li ◽

Yuanxun Shao

Keyword(s):

Neural Networks ◽

Fault Detection ◽

Chemical Processes ◽

Eastman Chemical

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An Intelligent Data Mining-Based Fault Detection and Classification Strategy for Microgrid

IEEE Access ◽

10.1109/access.2021.3056534 ◽

2021 ◽

Vol 9 ◽

pp. 22470-22479

Author(s):

Shazia Baloch ◽

Mannan Saeed Muhammad

Keyword(s):

Data Mining ◽

Fault Detection ◽

Fault Detection And Classification ◽

Classification Strategy

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Fault Detection and Classification of Power System Busbar using Artificial Neural Network

2019 IEEE International Conference on Power, Electrical, and Electronics and Industrial Applications (PEEIACON) ◽

10.1109/peeiacon48840.2019.9071944 ◽

2019 ◽

Author(s):

Adrita Anika ◽

Md. Junaed-Al-Hossain ◽

Sk. Hasibul Alam ◽

Nahid-Al-Masood

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Fault Detection ◽

Power System ◽

Fault Detection And Classification ◽

Artificial Neural

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Fault Detection and Classification in Power Electronic Circuits Using Wavelet Transform and Neural Network

Journal of Computer Science ◽

10.3844/jcssp.2011.95.100 ◽

2011 ◽

Vol 7 (1) ◽

pp. 95-100 ◽

Author(s):

Prasannamoorthy

Keyword(s):

Neural Network ◽

Wavelet Transform ◽

Fault Detection ◽

Power Electronic ◽

Electronic Circuits ◽

Fault Detection And Classification ◽

Power Electronic Circuits

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Spatiotemporal Pattern Modeling for Fault Detection and Classification in Semiconductor Manufacturing

IEEE Transactions on Semiconductor Manufacturing ◽

10.1109/tsm.2011.2172469 ◽

2012 ◽

Vol 25 (1) ◽

pp. 72-82 ◽

Author(s):

Hyung Jin Chang ◽

Dong Sung Song ◽

Pyo Jae Kim ◽

Jin Young Choi

Keyword(s):

Fault Detection ◽

Semiconductor Manufacturing ◽

Spatiotemporal Pattern ◽

Fault Detection And Classification ◽

Pattern Modeling

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