Abstract: The traditional underground power cable fault positioning method relies on subjective parameter selection and noise resistance is poor. It cannot meet the accurate fault positioning requirements of underground power cable under strong noise background. In order to solve the above problems, a fault positioning method of underground power cable based on salp swarm algorithm (SSA) optimizing variational mode decomposition (VMD) combined with novel Teager energy operator (NTEO) is proposed. In response to the problem of modal aliasing, over decomposition, and under decomposition in signal decomposition of VMD, SSA is used to optimize the modal number K and penalty factor α of VMD parameters using fuzzy entropy as the fitness function. The intrinsic modal function that better reflects the fault feature information is obtained. NTEO is used to calibrate the first wave head to obtain the arrival time of the wave heads at both ends. The fault position is determined based on the dual end distance measurement method. PSCAD/EMTDC is used for underground power cable fault simulation. It simulates underground fault signals with strong background noise. The results show the following points. ① After adding 9 dB and 12 dB noise to the ideal current signal, the signal-to-noise ratio of SSA-VMD is the lowest, and the Pearson correlation coefficient is the highest. It indicates that SSA-VMD can effectively preserve the characteristic information of the signal while minimizing noise. ② Under different transition resistances, the positioning precision of SSA-VMD-NTEO is relatively high. ③ Under different fault phase angles, although SSA-VMD-NTEO may have different sampling points, the positioning position remains unchanged and still maintains high precision. ④ SSA−VMD-NTEO can ensure high positioning precision at different fault distances. ⑤ Under high underground noise and a sampling frequency of 10 MHz, SSA-VMD-NTEO has significant advantages in positioning precision compared to wavelet modulus maximum and VMD+NTEO methods.