The invention discloses a cross-linked cable partial discharge mode identification method based on an SOM-BP combined neural network. An SOM neural network is used as a primary network, a BP neural network is used as a secondary network, and the SOM neural network and the BP neural network are connected in series to form an SOM-BP combined neural network model. A cross-linked cable partial discharge simulation experiment is conducted, third-order and fourth-order statistical characteristics of an ultra-wideband single discharge pulse time domain waveform are extracted as the discharge fingerprint, and identification of the cable partial discharge type is realized. The identification result shows that the identification rate for all modes is higher than 90% when the SOM-BP combined neural network is used as a classifier and the identification effect based on the network is optimal for either the individual recognition rate or the overall identification rate, and proves the effectiveness and reasonability of the combined model.