In order to solve the problems of low efficiency and inaccurate fault diagnosis in the operation and maintenance management of substations, a whole-process supervision method of automation equipment operation and maintenance based on digital twin is proposed. The system realizes panoramic perception and real-time monitoring by constructing high-precision virtual mapping of substations; introduces machine learning algorithms to give the system the ability of intelligent analysis and decision-making optimization; and applies human-computer interaction technology to enhance the experience of human-machine collaborative operation. The experimental results show that in the anomaly detection experiment, the algorithm achieves 95.2% precision and 97.1% recall on the test set, which indicates that the algorithm is able to effectively detect anomalies in the operation of the substation. The algorithm achieves 92.4% fault localization accuracy and 88.6% fault type identification accuracy on the test set.