10kV feeder line fault prediction method based on CNN and LightGBM

The invention discloses a 10kV feeder line fault prediction method based on a CNN (Convolutional Neural Network) and LightGBM (LightGBM), and the method mainly comprises the steps: 1), obtaining the original data of a power distribution network, and carrying out the preprocessing of the original data of the power distribution network; 2) extracting features from the original data of the power distribution network, and constructing a feature set f {f1, f2... F15, f16, L}, wherein L is a label and represents whether the feeder line has a fault or not, the element f1, the element f2, the elementf3, the element f4, the element f5 and the element f6 are inherent attribute characteristics, the element f7, the element f8, the element f9, the element f10, the element f11, the element f12 and theelement f13 are statistical analysis characteristics, and the element f14, the element f15 and the element f16 are depth time sequence features extracted by a convolutional neural network CNN; 3) establishing a power distribut