The accuracy of dynamic threshold is low by using the weighted average method. In order to solve this problem,a dynamics threshold calculation method for swashplate bearing based on Bayesian inference is proposed by using the characteristics of the probability density of normal data and different fault type data. Firstly,the singular value decomposition was used to preprocess the vibration signal,and the influence of noise on the dynamic threshold calculation result was filtered out.Secondly,the fault frequency energy feature extracting method was used to extract the features of normal data and inner ring,outer ring and ball fault data. Finally,Bayesian inference method was used to calculate the dynamic threshold of normal data and inner ring,outer ring and ball fault data respectively. The data were obtained by using the fault implantation method,and the dynamic threshold experiments were carried out. The experimental results show that the proposed method which has higher true positive rate and lower false positive rate can correctly find the dividing point between the probability density curve of normal data and different fault type data. The proposed method improves the calculation accuracy of dynamic threshold.