Design and Optimization of TL-DBN Model for Energy Saving Strategy of NC Machine Tools
The operation control performance of machine tools is affected by the actual workshop environment and production process conditions.How to improve the energy saving effect is a key to ensure the cost of machinery manufacturing.In order to improve the coordination ability of NC machine tools and realize the effect of energy saving,a transfer learning method was designed to realize the energy saving control process of CNC machine tools.The energy consumption control model of discrete CNC machine tool with RF driving function was established to reduce the energy consumed in the waiting stage.The results show that,compared with other algorithms,the decision error of TL-DBN model reaches the lowest value of 3.2％.The transfer learning process can optimize the effect of energy saving decision,and can make the machine tool achieve the ideal effect of energy saving.The control scheme of this study provides guidance for the realization of production process control and lays a certain theoretical foundation for the subsequent control optimization.
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