Abstract: Aiming at uncertainty and the poor generality of hydropower equipment fault diagnosis, a general situation assessment model based on Bayesian Networks is put forward. The model includes three levels, i.e., character level, understanding level, and assessment level. Nodes in Bayesian networks are divided into situation and event nodes according to their functions. During reasoning the information acquired by sensors are taken as the evidence of event node to update the probability of situation node and in turn, to influence the probability of event nodes. The diagnosis model in application of hydropower speed governor system shows that the veracity can be up to 95.2%, thus indicating the reliability provided by the situation assessment model.