随机任务驱动下机床间歇状态的动态节能控制方法

doi:10.3901/JME.2025.11.348

机械工程学报 ›› 2025, Vol. 61 ›› Issue (11): 348-360.doi: 10.3901/JME.2025.11.348

• 数字化设计与制造 • 上一篇

扫码分享

随机任务驱动下机床间歇状态的动态节能控制方法

江志刚¹, 祝青森¹, 朱硕², 鄢威³, 张华³

1. 武汉科技大学冶金装备及其控制教育部重点实验室武汉 430081;
2. 武汉科技大学机械传动与制造工程湖北省重点实验室武汉 430081;
3. 武汉科技大学绿色制造工程研究院武汉 430081

收稿日期:2024-06-21 修回日期:2024-12-28 发布日期:2025-07-12
作者简介:江志刚，男，1978年出生，博士，教授，博士研究生导师。主要研究方向为绿色制造、再制造。E-mail：jzg100@163.com;祝青森，男，1999年出生，硕士研究生。主要研究方向为绿色制造。E-mail：zhuqingsen01@163.com;朱硕(通信作者)，男，1989年生，博士，副教授，硕士研究生导师。主要研究方向为绿色制造、再制造。E-mail：zhushuo@wust.edu.cn;鄢威，男，1981年出生，博士，副教授，硕士研究生导师。主要研究方向为绿色制造。E-mail：15697180887@163.com;张华，女，1964年出生，博士，教授，博士研究生导师。主要研究方向为绿色制造、再制造、制造信息化。E-mail：zhanghua403@163.com
基金资助:
国家自然科学基金资助项目(52375508，HZKY20220338)。

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

JIANG Zhigang¹, ZHU Qingsen¹, ZHU Shuo², YAN Wei³, ZHANG Hua³

1. Key Laboratory of Metallurgical Equipment and Control Technology, Ministry of Education, Wuhan University of Science and Technology, Wuhan 430081;
2. Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering, Wuhan University of Science and Technology, Wuhan 430081;
3. Academy of Green Manufacturing Engineering, Wuhan University of Science and Technology, Wuhan 430081

Received:2024-06-21 Revised:2024-12-28 Published:2025-07-12

摘要/Abstract

摘要： 机床加工间歇期间的状态控制是提升机床节能效果的重要途径之一。针对当前未充分考虑随机任务情况对机床间歇状态控制的影响，导致机床在固定的节能控制策略下节能效果差的问题，提出一种随机任务驱动下机床间歇状态的动态节能控制方法。首先，分析随机任务下机床加工间歇的能耗模式，设计多种随机任务驱动下的机床间歇状态动态节能控制策略与切换机制；在此基础上，根据分析影响状态控制的关键因素建立随机任务加工环境信息样本集，构建堆栈去噪自编码节能控制模型，提取随机任务加工环境信息与机床节能控制策略紧密相关的深层特征，并作为SoftMax分类器的输入进行节能控制策略选择，以建立随机任务与机床节能控制策略的复杂映射关系，实现机床间歇状态的动态控制。最后以工件随机到达、新订单插入等随机任务为例进行验证。结果表明，所提方法能够实现机床间歇状态在随机任务引起的加工间歇长短改变情况下，节能、高效、准确地调整控制策略。

关键词: 随机任务, 动态控制, 加工间歇, 节能控制策略, 堆栈去噪自编码

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

中图分类号:

TH16

江志刚, 祝青森, 朱硕, 鄢威, 张华. 随机任务驱动下机床间歇状态的动态节能控制方法[J]. 机械工程学报, 2025, 61(11): 348-360.

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.

参考文献

[1] GAO K，HUANG Y，SADOLLA A，et al. A review of energy-efficient scheduling in intelligent production systems[J]. Complex Intell Syst 2020，6：237-249.
[2] SIHAG N，SANGWAN K S. A systematic literature review on machine tool energy consumption[J]. Journal of Cleaner Production，2020，275：123125.
[3] CAI W，LIU F，ZHOU X N，et al. Fine energy consumption allowance of workpieces in the mechanical manufacturing industry[J]. Energy，2016，114：623-633.
[4] CAI W，LIU F，XIE J，et al. An energy management approach for the mechanical manufacturing industry through developing a multi-objective energy benchmark[J]. Energy Conversion and Management，2017，132：361-371.
[5] PENG T，XU X. Energy-efficient machining systems：a critical review[J]. The International Journal of Advanced Manufacturing Technology，2014，72：1389-1406.
[6] WANG J，LI S，LIU J. A multi-granularity model for energy consumption simulation and control of discrete manufacturing system[C]//The 19th International Conference on Industrial Engineering and Engineering Management：Assistive Technology of Industrial Engineering. Springer Berlin Heidelberg，2013：1055-1064.
[7] MENG L，ZHANG C，SHAO X，et al. MILP models for energy-aware flexible job shop scheduling problem[J]. Journal of Cleaner Production，2019，210：710-723.
[8] MASHAEI M，LENNARTSON B. Energy reduction in a pallet-constrained flow shop through on-off control of idle machines[J]. IEEE Transactions on Automation Science and Engineering，2012，10(1)：45-56.
[9] 张朝阳，吉卫喜，彭威. 基于迁移学习的数控机床节能控制决策方法[J]. 中国机械工程，2020，31(23)：2855-2863. ZHANG Chaoyang，JI Weixi，PENG Wei. Decision making method for energy saving control of CNC machine tools based on transfer learning[J]. China Mechanical Engineering，2020，31(23)：2855-2863.
[10] RENNA P. Energy saving by switch-off policy in a pull-controlled production line[J]. Sustainable Production and Consumption，2018，16：25-32.
[11] FRIGERIO N，MATTA A. Analysis on energy efficient switching of machine tool with stochastic arrivals and buffer information[J]. IEEE Transactions on Automation Science and Engineering，2015，13(1)：238-246.
[12] ZHANG C，JIANG P. RFID-driven energy-efficient control approach of CNC machine tools using deep belief networks[J]. IEEE Transactions on Automation Science and Engineering，2019，17(1)：129-141.
[13] JIA Z，ZHANG L，ARINEZ J，et al. Performance analysis for serial production lines with Bernoulli machines and real-time WIP-based machine switch-on/off control[J]. International Journal of Production Research，2016，54(21)：6285-6301.
[14] SHROUF F，ORDIERES-MERE J，GARCIA-SANCHEZ A，et al. Optimizing the production scheduling of a single machine to minimize total energy consumption costs[J]. Journal of Cleaner Production，2014，67：197-207.
[15] GUO J，WANG L，KONG L，et al. Energy-efficient flow- shop scheduling with the strategy of switching the power statuses of machines[J]. Sustainable Energy Technologies and Assessments，2022，53：102649.
[16] 何彦，陈鹏文，鄢萍，等. 面向任务随机到达的机床节能运行方法[J]. 计算机集成制造系统，2016，22(4)：1029-1036. HE Yan，CHEN Pengwen，YAN Ping，et al.Energy-saving operation method of machine tool oriented to work piece random arrival[J]. Computer Integrated Manufacturing Systems，2016，22(4)：1029-1036.
[17] FRIGERIO N，MATTA A. Energy-efficient control strategies for machine tools with stochastic arrivals[J]. IEEE Transactions on Automation Science and Engineering，2014，12(1)：50-61.
[18] MARZANO L，FRIGERIO N，MATTA A. Energy efficient state control of machine tools：A time-based dynamic control policy[C]//2019 IEEE 15th International Conference on Automation Science and Engineering (CASE). IEEE. Vancouver，2019：596-601.
[19] FRIGERIO N，CORNAGGIA C F A，MATTA A. An adaptive policy for on-line energy-efficient control of machine tools under throughput constraint[J]. Journal of Cleaner Production，2021，287：125367.
[20] 侯文擎，叶鸣，李巍华. 基于改进堆叠降噪自编码的滚动轴承故障分类[J]. 机械工程学报，2018，54(7)：87-96 HOU Wenqing，YE Ming，LI Weihua. Rolling element bearing fault classification using improved stacked denoising autoencoders[J]. Journal of Mechanical Engineering，2018，54(7)：87-96.

随机任务驱动下机床间歇状态的动态节能控制方法

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

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 2

编辑推荐

Metrics

本文评价

[1]	刘德君;田彦涛;张雷. 双足欠驱动机器人能量成型控制[J]. , 2012, 48(23): 16-22.
[2]	胡里清;夏建伟;傅明竹;赵景辉;吴忻;葛栩栩;董辉. 运行参数的动态控制对100 kW燃料电池系统效率及稳定性的影响[J]. , 2005, 41(12): 48-53.