Energy consumption prediction system and method based on the decision tree for CNC lathe turning

Abstract

The present disclosure discloses a system and a method for predicting energy consumption in a numerically controlled lathe turning process based on a decision tree and belongs to the technical field of lathe control systems. According to the present disclosure, the energy consumption in the turning process of the numerically controlled lathe turning process based on mass historical data generated in the turning process, and the limit of specific workshop environmental factors such as lathe types and workpiece machining methods on a traditional energy consumption prediction algorithm is broken through; and the influence of various factors on turning energy consumption of a numerically controlled lathe is fully considered, a quantitative relationship between turning energy consumption and turning parameters is obtained by using a decision tree algorithm in a data mining technology and then combined with a self-correction module to correct a preliminary prediction result, and energy consumption in the numerically controlled lathe turning process is pre-calculated and used to guide an actual machining process. In addition, a model and a historical turning parameter database can be continuously updated according to actual conditions, so that the prediction precision of the prediction model is continuously improved, and an operator can select more reasonable turning parameters, thus finally helping enterprises to improve the machining efficiency.

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