To study the internal leakage of the hydraulic motor and monitor the state of the hydraulic motor. The fault data of the leakage in the hydraulic motor is obtained by establishing a simulation leakage fault test platform. A fault prediction model based on TS fuzzy neural network is established in MATLAB, and the experimental data is used for the training of the model and verify the prediction results. After analyzing the prediction results, the influence of different number of samples in model prediction on the accuracy of fault prediction is discussed. Where the data fluctuates greatly during the analysis, the relative error is large. After the study, it was found that by fitting the experimental data, using the same model for training and prediction, the difference between the accuracy of the prediction model and the prefit difference of different numbers of samples after fitting was discussed. The results show that although the larger the number of data trained by the model, the higher the accuracy of the prediction, but only a small amount of data is used for modeling after the data is fitted, the prediction can achieve higher precision. It provides a reference for fault analysis of small data samples.