Tool Vibration Monitoring of Deep Hole Drilling and Boring Machine Based on Recurrent Neural Network
In order to overcome the defect of tool condition monitoring,a variety of audio signals such as vibration and sound generated during machining were collected,and deep cycle neural network(RNN)was trained by balancing samples.Deep hole boring machine was used to carry out model verification,and the change of tool state was analyzed.The results show that in order to verify and analyze the monitoring effect of the model,a deep hole boring machine is used to test the model.The accuracy of the test results reached 98.4％,and the ideal monitoring effect was obtained.Compared with fuzzy PID and BP neural network,the recurrent neural network can not only reduce the noise but also retain the useful information of the signal itself.
deep hole drillingcondition monitoringrecurrent neural networkdiagnostic accuracy
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