Abstract: secondary equipment based on classification weighted association rules is studied. First of all，the automatic equipment operation and maintenance monitoring system is used to collect the relevant data of the substation secondary equipment，and extract the defect characteristics of the substation secondary equipment from the collected equipment data to build a defect model. Then，the defect model is used to form a transaction dataset，and the association rules that can be used for secondary equipment defect detection are mined from the transaction dataset. Based on this，the classification weighted association rule algorithm is used to assign different weights to different association rules to determine the classification weighted association rules. Finally，Apriori algorithm is used to output the defect detection results of secondary equipment in substation according to the classification weighted association rules. The experimental results show that this method can effectively mine the classification weighted association rules of secondary equipment defects in substations，and the defect detection accuracy is higher than 96%.