Dynamic process fault detection and diagnosis based on a combined approach of hidden Markov and Bayesian network model

Chemical Engineering Science ◽

10.1016/j.ces.2019.01.060 ◽

2019 ◽

Vol 201 ◽

pp. 82-96 ◽

Author(s):

Mihiran Galagedarage Don ◽

Faisal Khan

Keyword(s):

Fault Detection ◽

Bayesian Network ◽

Network Model ◽

Dynamic Process ◽

Hidden Markov ◽

Fault Detection And Diagnosis ◽

Combined Approach ◽

Bayesian Network Model ◽

Detection And Diagnosis

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A hybrid neural network model for rule generation and its application to process fault detection and diagnosis

Engineering Applications of Artificial Intelligence ◽

10.1016/j.engappai.2006.06.007 ◽

2007 ◽

Vol 20 (2) ◽

pp. 203-213 ◽

Author(s):

S.C. Tan ◽

C.P. Lim ◽

M.V.C. Rao

Keyword(s):

Neural Network ◽

Fault Detection ◽

Network Model ◽

Neural Network Model ◽

Fault Detection And Diagnosis ◽

Rule Generation ◽

Hybrid Neural Network ◽

Detection And Diagnosis

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A Hidden Markov Model application with Gaussian Mixture emissions for fault detection and diagnosis on a simulated AUV platform

OCEANS 2016 MTS/IEEE Monterey ◽

10.1109/oceans.2016.7761280 ◽

2016 ◽

Author(s):

Mariela De Lucas Alvarez ◽

David M. Lane

Keyword(s):

Fault Detection ◽

Markov Model ◽

Hidden Markov Model ◽

Hidden Markov ◽

Gaussian Mixture ◽

Fault Detection And Diagnosis ◽

Model Application ◽

Detection And Diagnosis

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Recurrent Neural Network Model with Self-Attention Mechanism for Fault Detection and Diagnosis

2019 Chinese Automation Congress (CAC) ◽

10.1109/cac48633.2019.8996824 ◽

2019 ◽

Author(s):

Rui Zhang ◽

Zhihua Xiong

Keyword(s):

Neural Network ◽

Fault Detection ◽

Network Model ◽

Recurrent Neural Network ◽

Neural Network Model ◽

Attention Mechanism ◽

Fault Detection And Diagnosis ◽

Detection And Diagnosis

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Fault detection and diagnosis for data incomplete industrial systems with new Bayesian network approach

Journal of Systems Engineering and Electronics ◽

10.1109/jsee.2013.00058 ◽

2013 ◽

Vol 24 (3) ◽

pp. 500-511 ◽

Author(s):

Zhengdao Zhang ◽

Jinlin Zhu ◽

Feng Pan

Keyword(s):

Fault Detection ◽

Bayesian Network ◽

Fault Detection And Diagnosis ◽

Network Approach ◽

Industrial Systems ◽

Detection And Diagnosis

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Fault detection and diagnosis of chiller using Bayesian network classifier with probabilistic boundary

Applied Thermal Engineering ◽

10.1016/j.applthermaleng.2016.06.153 ◽

2016 ◽

Vol 107 ◽

pp. 37-47 ◽

Author(s):

Suowei He ◽

Zhiwei Wang ◽

Zhanwei Wang ◽

Xiaowei Gu ◽

Zengfeng Yan

Keyword(s):

Fault Detection ◽

Bayesian Network ◽

Fault Detection And Diagnosis ◽

Bayesian Network Classifier ◽

Detection And Diagnosis

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Fault detection and diagnosis for missing data systems with a three time-slice dynamic Bayesian network approach

Chemometrics and Intelligent Laboratory Systems ◽

10.1016/j.chemolab.2014.07.009 ◽

2014 ◽

Vol 138 ◽

pp. 30-40 ◽

Author(s):

Zhengdao Zhang ◽

Feilong Dong

Keyword(s):

Missing Data ◽

Fault Detection ◽

Bayesian Network ◽

Dynamic Bayesian Network ◽

Fault Detection And Diagnosis ◽

Data Systems ◽

Network Approach ◽

Detection And Diagnosis

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Dynamic process fault detection and diagnosis based on dynamic principal component analysis, dynamic independent component analysis and Bayesian inference

Chemometrics and Intelligent Laboratory Systems ◽

10.1016/j.chemolab.2015.09.010 ◽

2015 ◽

Vol 148 ◽

pp. 115-127 ◽

Author(s):

Jian Huang ◽

Xuefeng Yan

Keyword(s):

Principal Component Analysis ◽

Bayesian Inference ◽

Fault Detection ◽

Independent Component Analysis ◽

Dynamic Process ◽

Principal Component ◽

Component Analysis ◽

Fault Detection And Diagnosis ◽

Dynamic Principal Component Analysis ◽

Detection And Diagnosis

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A new bearing fault detection and diagnosis scheme based on hidden Markov modeling of vibration signals

2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221) ◽

10.1109/icassp.2001.940324 ◽

2002 ◽

Author(s):

H. Ocak ◽

K.A. Loparo

Keyword(s):

Fault Detection ◽

Hidden Markov ◽

Fault Detection And Diagnosis ◽

Markov Modeling ◽

Vibration Signals ◽

Bearing Fault ◽

Bearing Fault Detection ◽

Hidden Markov Modeling ◽

Detection And Diagnosis

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Fault Detection for Medical Body Sensor Networks Under Bayesian Network Model

2015 11th International Conference on Mobile Ad-hoc and Sensor Networks (MSN) ◽

10.1109/msn.2015.21 ◽

2015 ◽

Author(s):

Haibin Zhang ◽

Jiajia Liu ◽

Rong Li

Keyword(s):

Sensor Networks ◽

Fault Detection ◽

Bayesian Network ◽

Network Model ◽

Body Sensor Networks ◽

Bayesian Network Model

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Fault Detection and Diagnosis in the DAMADICS Benchmark Actuator System – A Hidden Markov Model Approach

IFAC Proceedings Volumes ◽

10.3182/20080706-5-kr-1001.02102 ◽

2008 ◽

Vol 41 (2) ◽

pp. 12419-12424 ◽

Author(s):

Gustavo M. de Almeida ◽

Song W. Park

Keyword(s):

Fault Detection ◽

Markov Model ◽

Hidden Markov Model ◽

Hidden Markov ◽

Fault Detection And Diagnosis ◽

System A ◽

Actuator System ◽

Detection And Diagnosis ◽

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