Multi-sensor data fusion technology is widely used because of its multi-scale and in-depth processing of data. In order to reduce the impact of conflicting data on the fusion accuracy, this paper proposes a multi-sensor data fusion method based on hybrid strategy. Firstly, the conflict factor K in Dempster-Shafer(DS) evidence theory is introduced to group the evidence, and the evidence is retained for low conflict evidence, and the high conflict data is weighted and modified. The weighted correction method uses information entropy and Bray-Curtis distance to calculate the uncertainty and difference of evidence, and synthesizes the two to obtain the corrected weighted evidence. Finally, the weighted evidence is fused according to DS combination rules, and then fused with low-conflict data to obtain the final result. The experimental analysis results show that the method can obtain correct results for various conflict situations, and the accuracy rate in the face of high conflict evidence reaches 98.12%. At the same time, in the application of fault diagnosis, the accuracy of this method reaches 89.98%, which proves the effectiveness and practicability of this method.