R/inverters.R

In bnRep: A Repository of Bayesian Networks from the Academic Literature

#' inverters Bayesian Network
#'
#' Intelligent fault inference of inverters based on a three-layer Bayesian network.
#' @usage NULL
#'
#' @format
#' A discrete Bayesian network to infer the probable uncertain faults. Probabilities were given within the referenced paper. The vertices are:
#' \describe{
#' \item{AbnormalPulseVoltageWaveform}{(TRUE, FALSE);}
#' \item{APhaseFailure}{(TRUE, FALSE);}
#' \item{APhaseNegativeWaveFormDistortion}{(TRUE, FALSE);}
#' \item{APhasePositiveWaveFormDistortion}{(TRUE, FALSE);}
#' \item{BPhaseFailure}{(TRUE, FALSE);}
#' \item{BPhaseNegativeWaveFormDistortion}{(TRUE, FALSE);}
#' \item{BPhasePositiveWaveFormDistortion}{(TRUE, FALSE);}
#' \item{C1Failure}{(TRUE, FALSE);}
#' \item{C1VoltageAnomaly}{(TRUE, FALSE);}
#' \item{C2Failure}{(TRUE, FALSE);}
#' \item{C2VoltageAnomaly}{(TRUE, FALSE);}
#' \item{CapacitanceParameterWeakening}{(TRUE, FALSE);}
#' \item{CPhaseFailure}{(TRUE, FALSE);}
#' \item{CPhaseNegativeWaveFormDistortion}{(TRUE, FALSE);}
#' \item{CPhasePositiveWaveFormDistortion}{(TRUE, FALSE);}
#' \item{DCLinkFailure}{(TRUE, FALSE);}
#' \item{G1PulseMissing}{(TRUE, FALSE);}
#' \item{G2PulseMissing}{(TRUE, FALSE);}
#' \item{G3PulseMissing}{(TRUE, FALSE);}
#' \item{G4PulseMissing}{(TRUE, FALSE);}
#' \item{G5PulseMissing}{(TRUE, FALSE);}
#' \item{G6PulseMissing}{(TRUE, FALSE);}
#' \item{T1OC}{(TRUE, FALSE);}
#' \item{T2OC}{(TRUE, FALSE);}
#' \item{T3OC}{(TRUE, FALSE);}
#' \item{T4OC}{(TRUE, FALSE);}
#' \item{T5OC}{(TRUE, FALSE);}
#' \item{T6OC}{(TRUE, FALSE);}
#' \item{VoltageWaveFormAsymmetry}{(TRUE, FALSE);}
#'  }
#'
#' @return An object of class \code{bn.fit}. Refer to the documentation of \code{bnlearn} for details.
#' @keywords NULL
#' @importClassesFrom bnlearn bn.fit
#' @references Han, S., He, Y., Zheng, S., & Wang, F. (2019). Intelligent Fault Inference of Inverters Based on a Three-Layer Bayesian Network. Mathematical Problems in Engineering, 2019(1), 3653746.
"inverters"