Localization Error Analysis of Machine Tool Turntable Based on GA Optimized BP Neural Network
In order to improve the error compensation effect of CNC machine tool turntable,a BP neural network optimization process is designed by genetic algorithm(GA),and the positioning error model of turntable is established by adding coordinate parameters and moving speed index.The GA optimization BP model was constructed by Matlab software,and after the optimization weights and thresholds were obtained,the results were transplanted into DSP to carry out modeling and prediction,which greatly improved the prediction rate.The results show that the machine tool turntable has different positioning errors at different spatial positions and rates,and the overall change characteristics are more complex.The model built by GA optimization BP neural network can achieve higher accuracy,and the error residual range is-0.5～0.5 μ m,which meets the actual demand.The research is helpful to improve the positioning accuracy of the machine tool turntable and enhance the machining accuracy.
in-machine measurement systempositioning errorreal-time predictiondigital signal processor(DSP)genetic algorithm-back propagation network
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