In order to improve the accuracy and efficiency of wear condition recognition of mechanical equipment,an intelligent recognition method of wear particle images by using Deep Belief Network(DBN) model in deep learning with ferrograph analysis technology was proposed.The Restricted Boltzmann Machine(RBM) was built,which was used to pretrain the DBN,and initialize the parameters of DBN,so as to complete the construction of identification model.By using ferrography analysis technology,the ferrography image was prepared by a ferrography instrument and preprocessed to build the sample used for DBN.The parameters in DBN were studied,and the influence of the changes of every parameter on the model performance was observed to obtain the optimal values.The results show that the proposed method can quickly and accurately identify the wear types of equipment,and the recognition accuracy reaches more than 99%.