The invention discloses a power distribution network fault diagnosis method based on a random matrix and deep learning, and relates to the technical field of power distribution network fault diagnosis. According to the method, two basic tools of a random matrix theory and a deep learning technology are introduced to process a fault high-dimensional data set, wherein the random matrix theory has strict and flexible mathematical analysis capability in a high-dimensional space, and the deep learning technology has excellent high-dimensional data modeling capability; the high-dimensional characteristics of a fault are extracted by the random matrix theory and the deep learning technology; fault criterion is formed by adopting multi-feature fusion technology according to the extracted fault high-dimensional characteristics according to the process; the fault diagnosis model is constructed, effective fault diagnosis information can be obtained from the real-time data of the power distribution network through the fault diagnosis model, and fault real-time diagnosis is carried out according to the effective fault diagnosis information, so that the accuracy and the intelligent degree of thefault diagnosis of the power distribution network are improved.