The invention discloses a VMD and CNN-based cable early fault identification and classification method. The method comprises the following steps: step 1, obtaining a to-be-tested analog signal; step 2, selecting a bandwidth limiting factor alpha, a noise tolerance tau and a mode decomposition number K as parameters, and setting parameter values; step 3, performing variational mode decomposition onvarious analog signals, obtaining each mode and the center frequency thereof, and realizing frequency band division; step 4, extracting decomposition modal features and constructing feature vectors;step 5, inputting various signal feature vectors into the convolutional neural network, carrying out parameter modulation training and obtaining a classification result. By using the method, early faults and over-current disturbance of the cable can be accurately distinguished, cable maintenance is completed in time before the early faults become permanent faults, and stable operation of a power grid is maintained.