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

Bayesian Network Classifier ◽

Fault Detection and Diagnosis in a Bayesian Network classifier incorporating probabilistic boundary 1

IFAC-PapersOnLine ◽

10.1016/j.ifacol.2015.09.604 ◽

2015 ◽

Vol 48 (21) ◽

pp. 670-675 ◽

Cited By ~ 7

Author(s):

Mohamed Amine Atoui ◽

Sylvain Verron ◽

Abdessamad Kobi

Keyword(s):

Fault Detection ◽

Bayesian Network ◽

Bayesian Network Classifier ◽

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 ◽

Cited By ~ 5

Author(s):

Zhengdao Zhang ◽

Jinlin Zhu ◽

Feng Pan

Keyword(s):

Fault Detection ◽

Bayesian Network ◽

Network Approach ◽

Industrial Systems ◽

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 ◽

Cited By ~ 21

Author(s):

Zhengdao Zhang ◽

Feilong Dong

Keyword(s):

Missing Data ◽

Fault Detection ◽

Bayesian Network ◽

Dynamic Bayesian Network ◽

Time Slice ◽

Data Systems ◽

Network Approach ◽

Fault detection and diagnosis using Bayesian-network inference

IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society ◽

10.1109/iecon.2017.8216872 ◽

2017 ◽

Cited By ~ 1

Author(s):

Yuping Zhang ◽

Liyu You ◽

Chunhua Jia

Keyword(s):

Fault Detection ◽

Bayesian Network ◽

Network Inference ◽

Detection And Diagnosis ◽

Bayesian Network Inference

A Framework to Automate Fault Detection and Diagnosis Based on Moving Window Principal Component Analysis and Bayesian Network

Reliability Engineering & System Safety ◽

10.1016/j.ress.2021.107837 ◽

2021 ◽

pp. 107837

Author(s):

Arthur Henrique de Andrade Melani ◽

Miguel Angelo de Carvalho Michalski ◽

Renan Favarão da Silva ◽

Gilberto Francisco Martha de Souza

Keyword(s):

Principal Component Analysis ◽

Fault Detection ◽

Bayesian Network ◽

Principal Component ◽

Component Analysis ◽

Moving Window ◽

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 ◽

Cited By ~ 17

Author(s):

Mihiran Galagedarage Don ◽

Faisal Khan

Keyword(s):

Fault Detection ◽

Bayesian Network ◽

Network Model ◽

Dynamic Process ◽

Hidden Markov ◽

Combined Approach ◽

Bayesian Network Model ◽

Fault detection and diagnosis of chillers using Bayesian network merged distance rejection and multi-source non-sensor information

Applied Energy ◽

10.1016/j.apenergy.2016.11.130 ◽

2017 ◽

Vol 188 ◽

pp. 200-214 ◽

Cited By ~ 42

Author(s):

Zhanwei Wang ◽

Zhiwei Wang ◽

Suowei He ◽

Xiaowei Gu ◽

Zeng Feng Yan

Keyword(s):

Fault Detection ◽

Bayesian Network ◽

Sensor Information ◽

Wind turbine fault detection and diagnosis using LSTM neural network

2020 39th Chinese Control Conference (CCC) ◽

10.23919/ccc50068.2020.9188709 ◽

2020 ◽

Author(s):

Taoran Yang ◽

Jing Teng ◽

Changling Li ◽

Yizhan Feng

Keyword(s):

Neural Network ◽

Fault Detection ◽

Wind Turbine ◽

Fault Detection and Diagnosis of Induction Machine with On-Line Parameter Programming Facility

i-manager’s Journal on Instrumentation and Control Engineering ◽

10.26634/jic.2.1.2787 ◽

2014 ◽

Vol 2 (1) ◽

pp. 1-8

Author(s):

Sheikh Rafik Manihar Ahmed ◽

Keyword(s):

Fault Detection ◽

Induction Machine ◽

Line Parameter ◽

On Line ◽

Overview on hybrid approaches to fault detection and diagnosis: Combining data-driven, physics-based and knowledge-based models

Procedia CIRP ◽

10.1016/j.procir.2021.03.041 ◽

2021 ◽

Vol 99 ◽

pp. 278-283

Author(s):

Yannick Wilhelm ◽

Peter Reimann ◽

Wolfgang Gauchel ◽

Bernhard Mitschang

Keyword(s):

Fault Detection ◽

Data Driven ◽

Knowledge Based ◽

Hybrid Approaches ◽

Combining Data ◽