In order to further improve the fault diagnosis accuracy of fiber optic composite submarine cable, a fault diagnosis method based on VMD and SO optimization SVM is proposed. Firstly, VMD was used to decompose the fault data, several IMF components were obtained, and Pearson correlation coefficient was used for further screening. Secondly, feature extraction is carried out on the selected IMF components to extract the kurtosis, approximate entropy and fuzzy entropy of each component respectively. Finally, the eigenvectors composed of the above eigenvalues are input into the SVM optimized by SO for training and classification, and the fault diagnosis results are obtained. The experimental results show that the fault recognition accuracy of fiber-optic composite submarine cable can reach 100% by using the optimized SVM method based on VMD and SO, which is 7.5%, 5%, 5% and 7.5% higher than that of SVM, GA-SVM, GGO-SVM and CNN respectively.