Power transmission line fault identification method and system based on clustering and ensemble learning

The invention provides a power transmission line fault identification method and system based on clustering and ensemble learning, and the method comprises the steps: carrying out the voltage segmentation of power frequency voltage data of a processed power transmission line according to a time sequence through mean shift clustering, dividing the power frequency voltage data into A, B and C segments, the A segment being a normal waveform, the B segment being a fault or disturbance waveform, and the C segment being a trip or post-disturbance waveform; one periodic waveform of the section A and the section C are used for sliding window subtraction, then numerical values of windows are summed to obtain a new waveform N, and the amplitude of the waveform N represents the difference between the waveforms in the section A and the section C; the minimum value k of each period of the waveform N is taken, k represents the moment when the difference value is the minimum in a certain period in the A sliding window subtr