Dynamic Energy-saving Control Method for Intermittent State of Machine Tools Driven by Stochastic Tasks

doi:10.3901/JME.2025.11.348

Abstract

Abstract: The state control of machine tools during machining intervals is one of the important ways to improve the energy saving effect of machine tools. In view of the current problem that the impact of random tasks on the intermittent state control of machine tools is not fully considered, resulting in poor energy-saving effect of machine tools under fixed energy-saving control strategies, a dynamic energy-saving control method for intermittent state of machine tools driven by random tasks is proposed. First, the energy consumption patterns of machine tool intermittent processing under random tasks are analyzed, and various dynamic energy-saving control strategies and switching mechanisms for machine tool intermittent states driven by random tasks are designed; on this basis, a sample set of random task processing environment information is established based on the analysis of key factors affecting state control, a stacked denoising auto-encoder energy-saving control model is constructed, and the deep features of random task processing environment information closely related to machine tool energy-saving control strategies are extracted. The deep features closely related to the machine tool energy-saving control strategy are extracted and used as the input of SoftMax classifier for energy-saving control strategy selection, so as to a complex mapping relationship between the random task and the machine tool energy-saving control strategy is established and realize the dynamic control of the intermittent state of the machine tool. Finally, random tasks such as random arrival of workpieces and insertion of new orders are used as examples for validation. The results show that the proposed method is able to realize the energy-saving, efficient and accurate adjustment of the control strategy of the machine tool intermittent state under the change of the machining interval length caused by the random task.

Key words: stochastic task, dynamic control, processing interval, energy-saving control strategy, stacked denoising auto-encoders

CLC Number:

TH16

JIANG Zhigang, ZHU Qingsen, ZHU Shuo, YAN Wei, ZHANG Hua. Dynamic Energy-saving Control Method for Intermittent State of Machine Tools Driven by Stochastic Tasks[J]. Journal of Mechanical Engineering, 2025, 61(11): 348-360.

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