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Journal articles
Bayesian Network Method for Fault Diagnosis in a Continuous Tubular Reactor
Abstract : The aim is this paper is to study fault diagnosis in a continuous chemical process. An experimental system is built to be the research base and a model is proposed and trained to carry out the fault diagnosis in the process. A Bayesian network model with two-layer nodes structure is designed and Maximum likelihood estimation (MLE) is used to amend the conditional probability table (CPT) given by expert knowledge. Then a Monte Carlo method is applied to simplify the inference rules and the data samples collected from the experimental system has been used to test the model.
https://hal-normandie-univ.archives-ouvertes.fr/hal-02409976
Contributor : Isabelle Polaert <>
Submitted on : Friday, December 13, 2019 - 4:06:54 PM
Last modification on : Thursday, February 6, 2020 - 9:18:02 AM
Contributor : Isabelle Polaert <>
Submitted on : Friday, December 13, 2019 - 4:06:54 PM
Last modification on : Thursday, February 6, 2020 - 9:18:02 AM
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