Abstract: A fault location method of steam turbine rotor was proposed based on XGBoost algorithm. Firstly, the characteristics of the original sample set composed of fault types and related parameters were analyzed to evaluate the importance of each feature. Then, the XGBoost algorithm was used to build fault location model of steam turbine rotor, so as to use rotor fault data to train and test the model. Finally, specific fault causes were linked to the fault knowledge base, based on which, corresponding fault repair measures were taken. Results show that compared with random forest（RF） and gradient boosting decision tree（GBDT） model, XGBoost model can identify 9 fault causes of turbine rotor under three types of faults effectively, which shows higher classification accuracy.