Review paper
Fusion-Learning of Bayesian Network Models for Fault Diagnostics
Abstract
Bayesian Network (BN) models are being successfully applied to improve fault diagnosis, which in turn can improve equipment uptime and customer service. Most of these BN models are essentially trained using quantitative data obtained from sensors. However, sensors may not be able to cover all faults and therefore such BN models would be incomplete. Furthermore, many systems have maintenance logs that can serve as qualitative data, potentially...
Paper Details
Title
Fusion-Learning of Bayesian Network Models for Fault Diagnostics
Published Date
Nov 17, 2021
Journal
Volume
21
Issue
22
Pages
7633 - 7633
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