The invention belongs to the electric power system scheduling automation technology field and relates to a familial defect analysis method of equipment based on a clustering algorithm. The method comprises the following steps of (1) extracting N characteristics from equipment alarm information data and daily management data, forming the characteristics into one N-dimensional vector and completing mapping from an original data set to an N-dimensional vector space; (2) using characteristic standardization normalization method to process the data and eliminating an error brought by a data magnitude difference; (3) using a canopy algorithm to carry out ''rough '' polymerization on the data set so as to calculate a K value; (4) using a KMeans algorithm to carry out ''refined'' polymerization on the data set; (5) using a rough set algorithm to calculate a key attribute; (6) and using an elbow method to determine the K value. By using the method of the invention, manpower resource wastes are reduced; and algorithm and analysis replace original experience determination so that disposal efficiency of an event is increased.