The Construction of Turning Chatter Forecast Function Based on Elman Neural Network
In order to forecast the turning chatter phenomenon,a turning chatter forecast function is constructed.After analyzing the mechanism of regenerative chatter,a stability lobes diagram is obtained and provides the possibility of chatter forecast.The Elman neural network is used to train and test the time-domain signal from the stable turning stage to the turning chatter during the process of turning.The mean square error is proposed as the feature quantity for judging chatter.In order to predict the chatter more accurately,the sign function is used to construct the forecast function of regenerative turning chatter and the threshold of the forecast function is determined to be 5.625 and the prediction accuracy at the threshold of the forecast function is 92％.Finally,in the frequency domain,according to the characteristics of chatter,the validity of the constructed forecast function is verified.
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