Fault diagnosis based on Bayesian network for capacitive equipment

A fault diagnosis method based on Bayesian network is presented for capacitive equipment.The construction process of Bayesian network is expounded.The information of capacitive equipment fault are widely collected,and various detected data and fault symptoms are summarized to form a comprehensive fault set and symptom set.The conditional probability of each symptom clearly presented under different fault type is acquired,based on which,the fault diagnosis model based on Bayesian network is founded for capacitive equipment and the reasoning process of Bayesian network is improved.The probability calculation method is adopted and the fault type is diagnosed by the calculated probability,which improves its practicability.Its correctness and effectiveness are validated by the practical fault diagnosis results for capacitive equipment.