Research on CNC Machine Fault Diagnosis Based on Ant Colony Algorithm and Neural Network

In order to overcome the shortcomings of slow convergence speed and easy falling into the local minimum points in the BP neural network,based on the research of ant colony algorithm to optimizate neural network training algorithm,it takes CNC machine tool feed servo system fault diagnosis as example to establish the fault diagnosis model.The fault of feed servo system is diagnosed by trained ant colony neural network,and the training and diagnosis results of the BP neural network and the ant colony neural network are comparied.The result shows that the ant colony neural network has the advantages of more quick convergence speed,higher operation efficiency,stronger identification ability than BP neural network.These show that the ant colony neural used in the fault diagnosis of CNC machine tool,which can effectively improve the accuracy of fault diagnosis and efficiency,has good application prospects.