智能加工中数据使能技术与应用

doi:10.3901/JME.260064

机械工程学报 ›› 2026, Vol. 62 ›› Issue (2): 407-444.doi: 10.3901/JME.260064

• 交叉与前沿 • 上一篇

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智能加工中数据使能技术与应用

刘海波^1,2, 邓平^1,2, 迟庆宇^1,2, 刘天然^1,2, 刘阔^1,2, 李特^1,2, 黄祖广³, 刘行健^1,4, 薄其乐^1,2, STEVEN Y LIANG⁵, 王永青^1,2,6

1. 大连理工大学机械工程学院大连 116024;
2. 高性能精密制造全国重点实验室大连 116024;
3. 通用技术集团机床工程研究院有限公司北京 100102;
4. 大连理工大学机器人与智能系统研究院大连 116024;
5. 佐治亚理工学院乔治·W·伍德拉夫机械工程学院亚特兰大 30332 美国;
6. 智能制造龙城实验室常州 213164

收稿日期:2025-06-24 修回日期:2025-11-05 发布日期:2026-03-02
作者简介:刘海波,男,1984年出生,博士,教授,博士研究生导师。主要研究方向为测量-加工一体化、在机/在位精密测量、数据驱动智能加工、机器人辅助制造等。E-mail:hbliu@dlut.edu.cn;邓平,男,1998年出生,博士研究生。主要研究方向为数据驱动的智能加工。E-mail:dpdut@mail.dlut.edu.cn;王永青,男,1969年出生,博士,教授,博士研究生导师。主要研究方向为数控及数字化制造系统,数控机床精度保持性技术等。E-mail:yqwang@dlut.edu.cn

Technologies and Applications of Data Enablement in Intelligent Machining

LIU Haibo^1,2, DENG Ping^1,2, CHI Qingyu^1,2, LIU Tianran^1,2, LIU Kuo^1,2, LI Te^1,2, HUANG Zuguang³, LIU Xingjian^1,4, BO Qile^1,2, STEVEN Y LIANG⁵, WANG Yongqing^1,2,6

1. School of Mechanical Engineering, Dalian University of Technology, Dalian 116024;
2. State Key Laboratory of High-performance Precision Manufacturing, Dalian 116024;
3. Genertec Machine Tool Engineering Research Institute Co., Ltd., Beijing 100102;
4. Institute of Robotics and Intelligent Systems, Dalian University of Technology, Dalian 116024;
5. George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta 30332 USA;
6. Intelligent Manufacturing Longcheng Laboratory, Changzhou 213164

Received:2025-06-24 Revised:2025-11-05 Published:2026-03-02

摘要/Abstract

摘要： 智能加工作为制造业向高精度与自主化转型的核心方向，其发展高度依赖数据使能技术对多源异构数据的深度解析与智能决策支撑。系统梳理数据使能技术在智能加工领域的研究进展，提出涵盖“在机测量-信号预处理-特征提取-特征融合-数据治理”的全流程使能框架，并重点分析多源传感信息融合、云-雾-边协同计算和工艺知识动态迁移三大关键技术。研究表明，数据使能技术有效增强了加工过程的实时响应与鲁棒性，显著强化了对加工过程可控与质量一致的保障，并在多工业场景中推动了智能化水平的跃升。然而，复杂工艺场景下多物理场耦合建模困难、虚实映射保真度不足、小样本知识迁移效率低等瓶颈仍制约技术应用。针对上述挑战，所提出融合动态联邦学习与因果推理的未来技术路径，为制造业向认知化高阶阶段演进提供系统性研究视角。

关键词: 智能加工, 数据使能, 数字孪生, 智能算法, 机器学习

Abstract: Intelligent machining, as the core direction of manufacturing industry's transformation to high precision and autonomy, is highly dependent on data enablement technology for in-depth analysis of heterogeneous data from multiple sources and intelligent decision support. In this study, we systematically sort out the research progress of data enablement technology in the field of intelligent achining, put forward a full-process enabling framework covering “On-machine measurement-Signal pre-processingFeature extraction-Multi-source fusion-Data governance”, and analyze three key technologies, namely, multi-source sensing information fusion cloud-fog-edge collaborative computation, and dynamic migration of process knowledge. The study shows that the data enabling technology is effective and efficient. The study shows that data enablement technology effectively enhances the real-time response and robustness of the process, significantly strengthens the guarantee of process control and quality consistency, and promotes the leap of intelligence level in multiple industrial scenarios. However, bottlenecks such as the difficulty of modeling multi-physical field coupling in complex process scenarios, the lack of fidelity of virtual-reality mapping, and the low efficiency of knowledge migration from small samples still restrict the application of the technology. Aiming at the above challenges, this paper proposes a future technology path that integrates dynamic federated learning and causal reasoning to provide a systematic research perspective for the manufacturing industry to evolve to a higher-order stage of cognitization.

Key words: intelligent manufacturing, data enablement, digital twin, intelligent algorithms, machine learning

中图分类号:

TP242

刘海波, 邓平, 迟庆宇, 刘天然, 刘阔, 李特, 黄祖广, 刘行健, 薄其乐, STEVEN Y LIANG, 王永青. 智能加工中数据使能技术与应用[J]. 机械工程学报, 2026, 62(2): 407-444.

LIU Haibo, DENG Ping, CHI Qingyu, LIU Tianran, LIU Kuo, LI Te, HUANG Zuguang, LIU Xingjian, BO Qile, STEVEN Y LIANG, WANG Yongqing. Technologies and Applications of Data Enablement in Intelligent Machining[J]. Journal of Mechanical Engineering, 2026, 62(2): 407-444.

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智能加工中数据使能技术与应用

Technologies and Applications of Data Enablement in Intelligent Machining

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