polymorphic {bnRep} | R Documentation |
polymorphic Bayesian Network
Description
Reliability analysis of high-voltage drive motor systems in terms of the polymorphic Bayesian network.
Format
A discrete Bayesian network to depict the high-voltage drive motor system’s miscellaneous fault states. Probabilities were given within the referenced paper. The vertices are:
- PresenceAbrasiveParticles
(Normal, Degradation, Failed);
- ExcessiveSpeed
(Normal, Degradation, Failed);
- PoorLubrification
(Normal, Degradation, Failed);
- InappropriateClearance
(Normal, Degradation, Failed);
- HighTemperatureGluing
(Normal, Degradation, Failed);
- ScratchVibration
(Normal, Degradation, Failed);
- Indentation
(Normal, Degradation, Failed);
- ImproperLubrification
(Normal, Degradation, Failed);
- ImproperAssembly
(Normal, Degradation, Failed);
- Moisture
(Normal, Degradation, Failed);
- ExcessiveInterShaftCurrent
(Normal, Degradation, Failed);
- ChemicalCorrosion
(Normal, Degradation, Failed);
- HighFrequencyPulseVoltage
(Normal, Degradation, Failed);
- LocalizedHighTemperatures
(Normal, Degradation, Failed);
- PoorCooling
(Normal, Degradation, Failed);
- SeverePartialDischarges
(Normal, Degradation, Failed);
- SurfaceCorrosion
(Normal, Degradation, Failed);
- PlasticDeformation
(Normal, Degradation, Failed);
- CorrosionFailure
(Normal, Degradation, Failed);
- InsulationDeterioration
(Normal, Degradation, Failed);
- WearFault
(Normal, Degradation, Failed);
- SystemDegradation
(Normal, Degradation, Failed);
Value
An object of class bn.fit
. Refer to the documentation of bnlearn
for details.
References
Zheng, W., Jiang, H., Li, S., & Ma, Q. (2023). Reliability Analysis of High-Voltage Drive Motor Systems in Terms of the Polymorphic Bayesian Network. Mathematics, 11(10), 2378.