The fault diagnosis with one single sensor cannot comprehensively use the multi-sensor correlation information of fault signals for underwater thruster entanglement. To solve the real-time fault diagnosis problem that in the case of entanglement, a kind of fault diagnosis method based on the combination of current and rotational speed signal correlation analysis and Fuzzy C-means clustering (FCM) is proposed. Firstly, the collected current and speed signals of underwater thrusters under different states are normalized; Secondly, the correlation of normalized current and speed signals is calculated, and the correlation matrix is formed, and the sliding window of sampling series is adopted to calculate the correlation coefficient change over time between current and speed. Then a kind of Fuzzy C-means clustering method based on improved distance index is used to diagnose fault with correlation matrix elements. To verify the effectiveness of the proposed method, the sampling data in the case of propeller entanglement is used to verify the proposed fault detection method. The results show that the proposed method can fully extract the multi-sensor correlation information of underwater thrusters compared with the fault diagnosis method using only one signal using Support Vector Machine, and the feature extraction is more sufficient, effectively improving the accuracy of underwater thruster fault diagnosis.