The fault element diagnosis model of weighed directed bipartite graph based on Bayesian suspected degree

Aiming at overcoming the disadvantages, such as high computational complexity, difficulty of modeling and error of diagnosis, which are existed in the current fault diagnosis methods, this paper analyzes the relationship between the faults and symptoms, establishes a fault diagnosis model based on weighed directed bipartite graph in this paper. According to the statistical probability, this paper initializes the model. This paper also completes the symptom based on switch temporal logic, calculates the Bayesian suspected degree of fault, and finally outputs results of fault diagnosis.