Regular Neural Network Based Machining Parameters Optimization Model Of NC Machine Tool

Sanping Wang,Junwen Chen,Wei Yan,Yansong Wang

doi:10.1051/matecconf/201823201006

Sanping Wang, Junwen Chen + Show 2 more

Open Access

https://doi.org/10.1051/matecconf/201823201006

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Abstract

Energy consumption process is the basis for energy efficiency improvement of machine tools. Most of the existing researches focus on the static modelling of energy consumption of a machine tool; however, there are a few studies that paid attention to that how process parameters influence the energy consumption of machine tools during processing. It is noted that the process parameters can be selected to reduce energy consumption during machining processes without additional investment. In this paper, a characteristic energy consumption model for NC machine tool was proposed. Then, the mapping rule between process parameters and energy consumption of machine tool was studied, and the model was solved with the regular neural network (RNN). Finally, the result was verified with an experiment of milling the surface of aluminium block, which can effectively improve the energy efficiency of machine tool. The experiment results are shown that regular neural network is used to optimize the process parameters and process the same machining characteristics; we analyze the in machining process of machine tool based on the three cutting parameters, and then, a model of energy consumption. We employ to learn, and use this trained model to select optimal parameters.

Highlights

With the widespread use of NC machine tools, the problem of energy consumption has become a hot research topic nowadays
Machine tool is the foundation of equipment manufacturing, How to improve the energy efficiency of machine tools is an important trend for the manufacturing industry
Most scholars have analysed the energy efficiency of machine tools from machine tool processing technology, but few scholars have considered the energy consumption of machine tools combined with machining characteristics. [6]Because the machine tool is in different state during the whole cutting process, according to different state, we can establish machine tool energy consumption model

Summary

Introduction

With the widespread use of NC machine tools, the problem of energy consumption has become a hot research topic nowadays. EITCE 2018 machining the workpiece by NC milling machine, The no-load energy consumption is mainly affected by the setting of machine parameters, and cutting energy consumption is mainly affected by process parameters and workpiece materials, the load independent energy consumption mainly includes the fixed consumption of the machine parts, such as the fan motor, the servo system and the cooling pump, which are only affected by the open / stop state. (5) Among them, n, v , and a denote spindle speed, feed speed and cutting depth respectively.p 、p 、p 、and p respectively represent the starting instantaneous power of the machine tool, the no-load instantaneous power, the processing instantaneous power, and the downtime instantaneous power, respectively. The energy consumption and processing energy are the main consideration when studying the energy consumption of different processing characteristics

Modelling of energy consumption by regular neural network in processing

Experimental condition

Experimental scheme

Conclusion