难加工金属材料切削表面完整性预测与调控

doi:10.3969/j.issn.1004-132X.2026.03.001

中国机械工程 ›› 2026, Vol. 37 ›› Issue (3): 509-527.DOI: 10.3969/j.issn.1004-132X.2026.03.001

• 机械基础工程 •

难加工金属材料切削表面完整性预测与调控

刘战强¹^,²^,⁴(), 赵永耀¹^,²^,³(), 王兵¹^,², 赵金富¹^,², 刘安南¹^,³, 姚龙旭¹^,³

^1.山东大学机械工程学院, 济南, 250061
^2.山东大学金属成形高端装备与先进技术全国重点实验室, 济南, 250061
^3.山东大学高效洁净机械制造教育部重点实验室, 济南, 250061
^4.山东大学机电与信息工程学院, 威海, 264209

收稿日期:2025-06-24 出版日期:2026-03-25 发布日期:2026-04-08
通讯作者: 赵永耀
作者简介:刘战强，男，1969年生，教授、博士研究生导师。主要研究方向为切削加工理论。E-mail： melius@sdu.edu.cn
赵永耀*（通信作者），男，2002年生，硕士研究生。研究方向为金属切削加工。E-mail： sduzhaoyongyao@mail.sdu.edu.cn。
基金资助:
国家自然科学基金(92360311);山东大学公共技术平台仪器设备能力提升项目(ts20230104)

Prediction and Conditioning of Surface Integrity for Cutting Difficult-to-machine Metallic Materials

LIU Zhanqiang¹^,²^,⁴(), ZHAO Yongyao¹^,²^,³(), WANG Bing¹^,², ZHAO Jinfu¹^,², LIU Annan¹^,³, YAO Longxu¹^,³

^1.School of Mechanical Engineering，Shandong University，Jinan，250061
^2.State Key Laboratory for High-end Equipment and Advanced Technology of Metal Forming，Shandong University，Jinan，250061
^3.Key Laboratory of High Efficiency and Clean Mechanical Manufacture of Ministry of Education，Shandong University，Jinan，250061
^4.School of Mechanical，Electrical & Information Engineering，Shandong University，Weihai，Shandong，264209

Received:2025-06-24 Online:2026-03-25 Published:2026-04-08
Contact: ZHAO Yongyao

摘要/Abstract

摘要：

切削表面完整性是已加工表面层几何、物理、化学和机械性能的综合体现，由切削过程中的力热载荷及材料去除模式调控，直接影响零部件产品服役性能及寿命，深入研究调控策略对切削表面完整性的影响机制，是实现高完整性表面加工的基础，对优化难加工金属材料的切削工艺具有重要意义。从几何特征、微观组织结构和表面层力学特性的角度对难加工金属材料切削表面完整性指标进行分类，综述切削表面完整性预测模型建立的方法。阐述难加工金属材料切削表面完整性调控方法的研究进展，比较刀具优化、工艺优化、多能场辅助加工和预处理等对切削表面完整性的影响机制差异。对切削表面完整性预测模型的机制以及调控策略的通用性进行探讨，展望切削表面完整性未来研究重点。

关键词: 难加工金属, 已加工表面完整性分类, 表面完整性预测模型, 表面完整性调控策略

Abstract:

Machined surface integrity， a composite reflection of the geometric， physical， chemical， and mechanical properties of the machined surface layers， is dictated by the thermo-mechanics loads and material removal modes inherent to the cutting processes. This integrity directly governed the in-service performance and lifespan of engineered components. A thorough investigation into how conditioning strategies influenced surface integrity was therefore fundamental to realize high-integrity surfaces， and was critically important for optimizing the machining of difficult-to-cut metallic materials. This review began by categorizing the metrics of machined surface integrity for these materials based on three aspects： geometric features， microstructural evolution， and surface-layer mechanical properties， while also summarizing the approaches for developing predictive models. Subsequently， it elucidated research advancements in machined surface integrity conditioning strategies of difficult-to-cut metallic materials， critically comparing the distinct influence mechanisms of tool and process optimization， multi-energy field assisted machining， and workpiece pre-treatment on machined surface integrity. Finally， this paper explored the prediction accuracy of current models and the general applicability of conditioning strategies， offering an outlook on future research priorities.

Key words: difficult-to-cut metal, classification of machined surface integrity, surface integrity prediction model, surface integrity control strategy

中图分类号:

TG506

刘战强, 赵永耀, 王兵, 赵金富, 刘安南, 姚龙旭. 难加工金属材料切削表面完整性预测与调控[J]. 中国机械工程, 2026, 37(3): 509-527.

LIU Zhanqiang, ZHAO Yongyao, WANG Bing, ZHAO Jinfu, LIU Annan, YAO Longxu. Prediction and Conditioning of Surface Integrity for Cutting Difficult-to-machine Metallic Materials[J]. China Mechanical Engineering, 2026, 37(3): 509-527.

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链接本文: https://www.cmemo.org.cn/CN/10.3969/j.issn.1004-132X.2026.03.001

https://www.cmemo.org.cn/CN/Y2026/V37/I3/509

图/表 15

图1 切削过程表面粗糙度形成机制［8］

Fig.1 Formation mechanism of surface roughness in milling process［8］

图2 预测表面粗糙度的人工智能方法［16-18］

Fig.2 Artificial intelligence method for predicting surface roughness［16-18］

图3 晶粒细化机制［22］

Fig.3 Grain refinement mechanism［22］

图4 应变诱导马氏体相变的两个阶段［42］

Fig.4 Two stages of strain-induced martensitic transformation［42］

图5 切削表面残余应力建模方法

Fig.5 Modeling methods of residual stress on machined surface

图6 超级双相不锈钢的CEL模型［49］

Fig.6 CEL model of super duplex stainless steel［49］

表1 不同表面完整性调控方法的调控效果与调控机理

Tab.1 Effects and mechanisms of different surface integrity regulation methods

调控方法		调控效果	调控机理
刀具优化	刀具纹理改善	降低表面粗糙度，增大应变硬化程度，增大残余应力	改变加工过程中刀具与工件摩擦学行为
刀具优化	刀具深冷处理	调控表面粗糙度	提高刀具耐磨性，减小刀具磨损
工艺优化	加工参数优化	调控表面粗糙度，调控残余应力，调控应变硬化	基于加工参数与表面完整性映射关系，优化加工参数
	冷却润滑技术	降低表面粗糙度，减小晶粒细化程度，减小应变硬化程度	冷却技术抑制刀具磨损与加工表面热变形，同时抑制晶粒的生长；润滑技术降低加工摩擦
	后处理	调控表面粗糙度，增大晶粒细化程度，增大应变硬化程度	喷丸引起晶粒破裂，在后续车削加工中位错迅速积累，导致晶粒细化程度更高；抛光处理去除车削产生的塑性变形层；滚压压力导致塑性变形
多能场辅助加工	激光辅助加工	调控表面粗糙度，增大晶粒细化程度，增大压缩残余应力	激光引起材料软化，切削力进而减小，导致工件表面微观组织结构变化减少；激光功率影响刀具磨损，调控表面粗糙度
	超声辅助加工	调控表面粗糙度，增大应变硬化程度	超声振动导致断续切削，同时刀具持续冲击工件，加剧应变硬化
	超声激光辅助加工	降低表面粗糙度	超声激光耦合减小刀具磨损，同时实现脆性材料的延性切削
表面预处理		降低表面粗糙度，减小应变硬化	Rehbinder效应

图7 球头铣刀前刀面微织构参数［4］

Fig.7 Micro-texture parameters of the rake face of ball-end milling cutter ［4］

图8 不同深冷工艺对表面粗糙度的影响［72］

Fig.8 Effect of different cryogenic processes on surface roughness［72］

图9 不同条件下表面粗糙度随切削速度变化趋势［75］

Fig.9 Trend of surface roughness with cutting speed under different conditions［75］

图10 LCO₂与LN₂冷却辅助钻削钛合金对比［92］

Fig.10 Comparison of LCO₂ and LN₂ cooling-assisted drilling of titanium alloy［92］

图11 耦合超声、激光的多能场辅助加工

Fig.11 Multi-energy field assisted processing by coupling ultrasound and laser

图12 超声振动辅助加工切削原理以及对切削表面的影响［121］

Fig.12 Ultrasonic vibration assisted machining cutting principle and its influence on cutting surface［121］

图13 墨水-金属界面引起的晶粒内部位错堆积［140］

Fig.13 Dislocation accumulation inside grains caused by ink-metal interface［140］

2026工业母机产业链高质量发展大会（一号通知）

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难加工金属材料切削表面完整性预测与调控

Prediction and Conditioning of Surface Integrity for Cutting Difficult-to-machine Metallic Materials

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