With the development of information and communication technology (ICT),the application of artificial intelligence techniques in machinery fault diagnosis has attracted the attention of researchers.In order to verify the trialability of artificial intelligence technology in machine tool spindle fault diagnosis,a test bench was constructed to collect the fault data by artificially changing the spindle eccentricity,and three kinds of artificial intelligence models (CNN,LSTM and AE) were used for learning,and their accuracy in classifying seven kinds of spindle fault states was analyzed and compared.The experimental results show that both CNN and LSTM models have high accuracy,with the CNN model achieving the highest accuracy at 99.3%,while the AE model has a relatively low accuracy of 76.9%.The feasibity of applying artificial intelligence technology in machine tool spindle fault diagnosis in verified.