Fault Diagnosis in Partially Observable Petri Nets with Quantum Bayesian Learning

Fault Diagnosis in Partially Observable Petri Nets with Quantum Bayesian Learning

This paper investigates the quantum Bayesian probability estimation of fault diagnosis based on Partially Observable Petri Nets (POPN) for a liquid-propellant rocket engine system. To solve the problem of a poor environment, a complex structure, and limited observable information in the liquid-prope...

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Bibliographic Details
Main Authors: Jiufu Liu, Elishahidi S. B. Mvungi, Xinzhe Zhang, Aurea Dias
Format: Article
Language:English
Published: MDPI AG 2023-12-01
Series:Applied Sciences
Subjects:
fault diagnosis
Petri nets
partially observed
quantum Bayesian learning
quantum interference
Online Access:https://www.mdpi.com/2076-3417/14/1/52

Internet

https://www.mdpi.com/2076-3417/14/1/52

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