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Geometric Model Reconstruction and Machining Error Control for Repair Technologies of Damaged Blisk Blades: Recent Advances and Future Trends
FORUM | 更新时间：2026-06-16
|
Geometric Model Reconstruction and Machining Error Control for Repair Technologies of Damaged Blisk Blades: Recent Advances and Future Trends
- Aeronautical Manufacturing Technology Vol. 69, Issue 10, Pages: 54-74(2026)
- 作者机构：
西北工业大学航空发动机高性能制造工信部重点实验室，西安 710072
西北工业大学航空发动机先进制造技术教育部工程研究中心，西安 710072
西北工业大学硬质合金全国重点实验室，西安 710072
中国航发动力股份有限公司，西安 710021
西安西航集团莱特航空制造技术有限公司，西安 710018
- 作者简介：
- 基金信息：
DOI：10.16080/j.issn1671-833x.25010186
CLC： V232Received：15 December 2025，
Revised：2026-01-12，
Accepted：02 February 2026，
Published：15 May 2026
- 稿件说明：
移动端阅览
引文格式：党稼宁，范凌松，李飞，等.整体叶盘损伤叶片修复加工的几何模型重构与加工误差控制技术研究进展[J].航空制造技术，2026, 69（10）：25010186.
DANG Jianing, FAN Lingsong, LI Fei, et al. Geometric model reconstruction and machining error control for repair technologies of damaged blisk blades: Recent advances and future trends[J]. Aeronautical Manufacturing Technology, 2026, 69(10): 25010186.
引文格式：党稼宁，范凌松，李飞，等.整体叶盘损伤叶片修复加工的几何模型重构与加工误差控制技术研究进展[J].航空制造技术，2026, 69（10）：25010186. DOI： 10.16080/j.issn1671-833x.25010186.
DANG Jianing, FAN Lingsong, LI Fei, et al. Geometric model reconstruction and machining error control for repair technologies of damaged blisk blades: Recent advances and future trends[J]. Aeronautical Manufacturing Technology, 2026, 69(10): 25010186. DOI： 10.16080/j.issn1671-833x.25010186.
Geometric Model Reconstruction and Machining Error Control for Repair Technologies of Damaged Blisk Blades: Recent Advances and Future Trends
摘要
整体叶盘作为新一代航空发动机的核心部件，其一体化轻量结构在提升推重比和气动效率方面优势显著。然而，在极端服役环境下，叶片易遭受外物打击、高温氧化、高周疲劳等多种损伤。由于一体化结构特性，受损叶片无法单独更换，使得维护成本高昂，严重制约了整体叶盘的批产应用。叶片修复加工技术可高效、低成本地恢复损伤叶片性能、延长服役寿命，已成为推动整体叶盘大规模应用的关键使能技术。本文综述了整体叶盘损伤叶片修复加工技术的研究现状与发展方向，在介绍叶片损伤类型与修复工艺流程的基础上，分析了损伤叶片几何模型重构与气动性能提升的理论方法，进而围绕损伤叶片修复加工弹性变形控制问题，归纳了薄壁零件铣削加工弹性变形预测和弹性变形补偿的研究进展及存在问题，最后展望了损伤叶片修复加工未来发展趋势。
Abstract
As a critical component of next-generation aero-engines
the blisk offers substantial advantages in thrustto-weight ratio and aerodynamic efficiency owing to its monolithic lightweight architecture. However
under extreme operating conditions
blisk blades are highly susceptible to various forms of damage
including foreign object damage
hightemperature oxidation
and high-cycle fatigue. The inherent monolithic nature of the blisk precludes the replacement of individual damaged blades
resulting in prohibitively high maintenance costs that severely impede its large-scale production and deployment. Blade repair and remanufacturing technology provides an efficient and cost-effective pathway to restore the performance of damaged blades and extend their service life
and has thus emerged as a key enabling technology for the widespread engineering application of blisks. This paper presents a review of the current research status and future development directions of blisk blade repair technology. Building upon an introduction to blade damage typology and repair process workflows
the theoretical methodologies for geometric model reconstruction and aerodynamic performance recovery of damaged blades are systematically analyzed. Subsequently
with a focus on elastic deformation control during blade repair machining
the research advances and existing challenges in elastic deformation prediction and compensation for thin-walled component milling are thoroughly examined. Finally
prospective development trends in damaged blade repair and remanufacturing technology are discussed.
关键词
Keywords
references
YANG H Q, SHAN Z D, WU R M, et al. Research progress on additive manufacturing technology and equipment for the vat polymerization of ceramic cores of aeroengine blades[J]. Additive Manufacturing Frontiers, 2025, 4(2): 200204.
刘大响，程荣辉.世界航空动力技术的现状及发展动向[J].北京航空航天大学学报，2002, 28(5): 490-496.
LIU Daxiang, CHENG Ronghui. Current status and development direction of aircraft power technology in the world[J]. Journal of Beijing University of Aeronautics and Astronautics, 2002, 28(5): 490-496.
刘大响，金捷，彭友梅，等.大型飞机发动机的发展现状和关键技术分析[J].航空动力学报，2008, 23(6): 976-980.
LIU Daxiang, JIN Jie, PENG Youmei, et al. Summarization of development status and key technologies for large airplane engines[J]. Journal of Aerospace Power, 2008, 23(6): 976-980.
姚倡锋，田卫军，任军学，等.航空发动机薄壁件铣削加工动力学研究进展[J].航空制造技术，2015, 58(22): 40-46.
YAO Changfeng, TIAN Weijun, REN Junxue, et al. Research progress on milling dynamics of aeroengine thin-walled parts[J]. Aeronautical Manufacturing Technology, 2015, 58(22): 40-46.
张定华，张仲玺，罗明，等.面向航空复杂薄壁零件智能加工的进化建模方法[J].航空制造技术，2016, 59(16): 93-98.
ZHANG Dinghua, ZHANG Zhongxi, LUO Ming, et al. Evolution modeling of intelligent machining for complex thin-walled parts[J]. Aeronautical Manufacturing Technology, 2016, 59(16): 93-98.
ZHOU H, LI X Q, SHAO C J, et al. Review on the automated fiber placement process for the aero-engine composite fan blade and its feasibility in element level[J]. Composites Part A:Applied Science and Manufacturing, 2025, 193:108875.
张高，刘梅军，韩嘉琪，等.压气机整体叶盘修复再制造的研究进展[J].航空材料学报，2024, 44(3): 65-81.
ZHANG Gao, LIU Meijun, HAN Jiaqi, et al. Research progress in repair and remanufacture of compressor blisk[J]. Journal of Aeronautical Materials, 2024, 44(3): 65-81.
黄春峰.现代航空发动机整体叶盘及其制造技术[J].航空制造技术，2006, 49(4):94-100.
HUANG Chunfeng. Modern aeroengine integral blisk and its manufacturing technology[J]. Aeronautical Manufacturing Technology, 2006, 49(4): 94-100.
白瑞金，张利国.涡轮叶片修复及其市场分析[J].航空制造技术，2002, 45(12): 37-40.
BAI Ruijin, ZHANG Liguo. Turbine blade repairing and its market analysis[J]. Aeronautical Manufacturing Technology, 2002, 45(12): 37-40.
张财伟，曹家洺，刘士伟，等.激光增材修复技术在发动机修复中的应用综述： 现状、挑战与展望[J].金属加工(热加工), 2025(2):20-27, 33.
ZHANG Caiwei, CAO Jiaming, LIU Shiwei, et al. A review of laser additive repair technology in engine restoration: Current status, challenges and perspectives[J]. MW Metal Forming, 2025(2):20-27, 33.
李鹏涛，左洪福，肖文，等.航空发动机叶片损伤及其修复技术研究与展望[J].航空学报，2024, 45(15): 132-159.
LI Pengtao, ZUO Hongfu, XIAO Wen, et al. Research and prospect of aero engine blade damage and its repair technology[J]. Acta Aeronautica et Astronautica Sinica, 2024, 45(15):132-159.
刘源泉.轴流压气机叶片综合参数化及气动优化研究[D].大连： 大连理工大学，2021: 16-23.
LIU Yuanquan. Research on comprehensive parameterization and aerodynamic optimization for axial compressor blades[D]. Dalian: Dalian University of Technology, 2021: 16-23.
吴永鑫.压气机串列叶栅实验及其损失控制机理研究[D].哈尔滨： 哈尔滨工业大学，2021: 13-16.
WU Yongxin. Research on experiment and loss control mechanism for tandem cascades[D]. Harbin: Harbin Institute of Technology, 2021:13-16.
DU Q W, LI Y Z, YANG L K, et al. Performance prediction and design optimization of turbine blade profile with deep learning method[J]. Energy, 2022, 254: 124351.
程超，吴宝海，郑海，等.叶片加工误差对压气机性能的影响[J].航空学报，2020, 41(2): 623237.
CHENG Chao, WU Baohai, ZHENG Hai, et al. Effect of blade machining errors on compressor performance[J]. Acta Aeronautica et Astronautica Sinica, 2020, 41(2): 623237.
李欣蔚.轴流压气机叶片气动性能优化设计[D].哈尔滨： 哈尔滨工程大学，2020:13-14.
LI Xinwei. Optimal design of axial compressor blade aerodynamic performance[D]. Harbin: Harbin Engineering University, 2020:13-14.
MA C, GAO L M, WANG H H, et al. Influence of leading edge with real manufacturing error on aerodynamic performance of high subsonic compressor cascades[J]. Chinese Journal of Aeronautics, 2021, 34(6): 220-232.
傅国如，禹泽民，王洪伟.航空涡喷发动机压气机转子叶片常见失效模式的特点与规律[J].国外金属加工，2006, 1(1): 18-24.
FU Guoru, YU Zemin, WANG Hongwei.Main failure attributes and rule of compressorblades in aero-engines[J]. Journal of International Metal Working, 2006, 1(1): 18-24.
GRACIANO D M, RODRÍGUEZ J A, URQUIZA G, et al. Damage evaluation and life assessment of steam turbine blades[J]. Theoretical and Applied Fracture Mechanics, 2023, 124:103782.
POURSAEIDI E, BABAEI A, MOHAMMADI ARHANI M R, et al. Effects of natural frequencies on the failure of R1 compressor blades[J]. Engineering Failure Analysis, 2012, 25:304-315.
BISWAS S, GANESHACHAR M D, KUMAR J, et al. Failure analysis of a compressor blade of gas turbine engine[J]. Procedia Engineering, 2014, 86: 933-939.
MISHRA R K, THOMAS J, SRINIVASAN K, et al. Fatigue failure of LP compressor blade in an aero gas turbine engine[J]. Journal of Failure Analysis and Prevention, 2014, 14(3): 296-302.
舒畅，程铭，许煜，等.航空发动机压气机叶片外物损伤规律研究[J].机械工程学报，2019, 55(13): 87-94.
SHU Chang, CHENG Ming, XU Yu, et al. Study on foreign object damage regular pattern of aero engine compressor blades[J]. Journal of Mechanical Engineering, 2019, 55(13): 87-94.
CARTER T J. Common failures in gas turbine blades[J]. Engineering Failure Analysis, 2005, 12(2): 237-247.
SILVEIRA E, ATXAGA G, IRISARRI A M. Failure analysis of a set of compressor blades[J]. Engineering Failure Analysis, 2008, 15(6): 666-674.
INFANTE V, FREITAS M. Failure analysis of compressor blades of a helicopter engine[J]. Engineering Failure Analysis, 2019, 104: 67-74.
张海兵，张泰峰，郭奇.航空发动机压气机叶片损伤分析与监控对策[J].无损检测，2021, 43(1): 15-18, 52.
ZHANG Haibing, ZHANG Taifeng, GUO Qi. Damage analysis and monitoring measures of compressor blades of an aero engine[J]. Nondestructive Testing, 2021, 43(1): 15-18, 52.
LOURENÇO N J, GRAÇA M L A, FRANCO L A L, et al. Fatigue failure of a compressor blade[J]. Engineering Failure Analysis, 2008, 15(8): 1150-1154.
INFANTE V, SILVA J M, DE FREITAS M, et al. Failures analysis of compressor blades of aeroengines due to service[J].Engineering Failure Analysis, 2009, 16(4): 1118-1125.
KERMANPUR A, SEPEHRI AMIN H, ZIAEI-RAD S, et al. Failure analysis of Ti6Al4V gas turbine compressor blades[J]. Engineering Failure Analysis, 2008, 15(8): 1052-1064.
刘庆瑔.发动机Ⅰ级压气机转子叶片断裂分析[J].失效分析与预防，2007, 2(2):34-36, 15.
LIU Qingquan. Fracture analysis on rotor blades of compressor Ⅰ for a series engines[J]. Failure Analysis and Prevention, 2007, 2(2):34-36, 15.
傅国如，杨兴宇.某型发动机压气机二级叶片断裂故障分析[J].宇航材料工艺，2000(Z): 63-67.
FU Guoru, YANG Xingyu. Fracture failure analysis of second stage compressor blade of a certain type engine[J]. Aerospace Materials &Technology, 2000(Z): 63-67.
范顺昌，唐晓辉，张银东，等.航空发动机高压压气机三级转子叶片掉角分析[J].失效分析与预防，2014, 9(2): 110-114.
FAN Shunchang, TANG Xiaohui, ZHANG Yindong, et al. Failure analysis of third-stage rotor blade of high-pressure compressor in aeroengine[J]. Failure Analysis and Prevention, 2014, 9(2): 110-114.
高志坤，胡霖，张开阔，等.某高压压气机第4 级转子叶片断裂分析[J].航空发动机，2019, 45(6): 85-89.
GAO Zhikun, HU Lin, ZHANG Kaikuo, et al. Failure analysis of 4th rotor blade of highpressure compressor[J]. Aeroengine, 2019, 45(6):85-89.
ZHANG H B, HU D Y, YE X B, et al. Experimental and analytical modelling on aeroengine blade foreign object damage[J]. International Journal of Impact Engineering, 2024, 183: 104813.
ZHANG H B, HU D Y, YE X B, et al. Prediction on aeroengine blade foreign object damage validated by air Gun tests[J]. Engineering Failure Analysis, 2023, 143: 106919.
康继东，陈士煊，徐志怀，等.压气机叶片外物损伤及其维修性的研究进展[J].燃气涡轮试验与研究，1998, 11(1): 59-62.
KANG Jidong, CHEN Shixuan, XU Zhihuai, et al. Research progress on foreign body damage and maintainability of compressor blades[J]. Gas Turbine Experiment and Research, 1998, 11(1):59-62.
张栋.失效分析[M].北京： 国防工业出版社，2004: 6-7.
ZHANG Dong. Failure analysis[M]. Beijing:National Defense Industry Press, 2004: 6-7.
黄耀祖．现役喷发动机压气机转子叶片外击损伤故障分析[C]//中国航空学会动力分会可靠性专业委员会航空发动机可靠性学术会议．北京： 中国航空学会， 2000.
HUANG Yaozu. Failure analysis of foreign object damage of compressor rotor blades in service turbojet engine[C]//Aircraft Engine Reliability Academic Conference of the Reliability Professional Committee, Power Branch, Chinese Society of Aeronautics and Astronautics. Beijing:Chinese Society of Aeronautics and Astronautics, 2000.
POURSAEIDI E, PEDRAM O. An outrun competition of corrosion fatigue and stress corrosion cracking on crack initiation in a compressor blade[J]. International Journal of Engineering-Transactions B: Applications, 2014, 27(5): 785-792.
PARKER J G. ‘Stress corrosion cracking and corrosion fatigue of steam-turbine rotor and blade materials'[J]. British Corrosion Journal, 1991, 26(3): 170-172.
PEDRAM O, POURSAEIDI E. Total life estimation of a compressor blade with corrosion pitting, SCC and fatigue cracking[J]. Journal of Failure Analysis and Prevention, 2018, 18(2): 423-434.
XIE Y J, WANG M C, ZHANG G, et al. Analysis of superalloy turbine blade tip cracking during service[J]. Engineering Failure Analysis, 2006, 13(8): 1429-1436.
WEI Y W, LI Y J, LAI J F, et al. Analysis on corrosion fatigue cracking mechanism of 17-4PH blade of low pressure rotor of steam turbine[J]. Engineering Failure Analysis, 2020, 118: 104925.
TURNBULL A, ZHOU S. Pit to crack transition in stress corrosion cracking of a steam turbine disc steel[J]. Corrosion Science, 2004, 46(5): 1239-1264.
王鹏，李锋，马康民.某型发动机压气机转子叶片失效分析[J].航空维修与工程，2005(4): 48-49.
WANG Peng, LI Feng, MA Kangmin. Failure analysis for compressor blades of aeroengine[J]. Aviation Maintenance & Engineering, 2005(4): 48-49.
HE B Y, KATSAMENIS O L, MELLOR B G, et al. 3-D analysis of fatigue crack behaviour in a shot peened steam turbine blade material[J]. Materials Science and Engineering: A,2015, 642: 91-103.
BISWAL R, SYED A K, ZHANG X. Assessment of the effect of isolated porosity defects on the fatigue performance of additive manufactured titanium alloy[J]. Additive Manufacturing, 2018, 23:433-442.
LAMBERT J, CHAMBERS A R, SINCLAIR I, et al. 3D damage characterisation and the role of voids in the fatigue of wind turbine blade materials[J]. Composites Science and Technology, 2012, 72(2): 337-343.
GOULD B, DEMAS N G, GRECO A C. The influence of steel microstructure and inclusion characteristics on the formation of premature bearing failures with microstructural alterations[J]. Materials Science and Engineering:A, 2019, 751: 237-245.
马劲夫，许进升.某型航空发动机压气机二级转子叶片掉块故障分析[J].航空维修与工程，2020(4): 79-80.
MA Jinfu, XU Jinsheng. Fault analysis on the secondary rotor blade chippling of compressor for a certain type of aero-engine[J]. Aviation Maintenance & Engineering, 2020(4): 79-80.
KANISHKA K, ACHERJEE B. A systematic review of additive manufacturingbased remanufacturing techniques for component repair and restoration[J]. Journal of Manufacturing Processes, 2023, 89: 220-283.
BREMER C. Automated repair and overhaul of aero-engine and industrial gas turbine components[C]//ASME Turbo Expo 2005: Power for Land, Sea, and Air. Reno, 2008: 841-846.
ZHENG J M, LI Z G, CHEN X. Worn area modeling for automating the repair of turbine blades[J]. The International Journal of Advanced Manufacturing Technology, 2006, 29(9-10):1062-1067.
党稼宁.面向整体叶盘损伤叶片修复加工的几何建模与轮廓精度控制技术[D].西安： 西北工业大学，2026.
DANG Jianing. The geometry modeling and profile machining precision control technology for repairing damaged blades of blisk[D]. Xi'an:Northwestern Polytechnical University, 2026.
ZHOU Y H, CHEN P H, HUANG D N, et al. Micro-arc oxidation for improving hightemperature oxidation resistance of additively manufacturing Ti 2 AlNb[J ] . Surface and Coatings Technology, 2022, 445: 128719.
MING X W, WU Y, ZHANG Z Y, et al. Micro-arc oxidation in titanium and its alloys: Development and potential of implants[J]. Coatings, 2023, 13(12): 2064.
QIN Z Y, ZHANG X G, ZHANG Y L, et al. Friction and wear characteristics of micro-arc oxidation coating on Ti6Al4V alloy—a review[J]. Biosurface and Biotribology, 2025, 11: e70000.
YUAN M C, LI Z L. Recent patents of micro-arc oxidation technology[J]. Recent Patents on Engineering, 2024, 18(6): e300423216386.
HU Y Z, WANG H S, WANG D H, et al. High-performance bioceramic coatings of 3D printed titanium alloys via FS-auxiliary micro-arc oxidation manufacturing[J]. Journal of Manufacturing Processes, 2024, 119: 337-347.
BORDBAR-KHIABANI A. Advances in anticorrosion and anti-wear plasma electrolytic oxidation coatings for titanium and its alloys[M]//SAJI V S, ZHELUDKEVICH M. Plasma Electrolytic Oxidation - Fundamentals, Advances and Applications: Edition Details. Cham: Springer Nature Switzerland, 2025: : 385-427.
SHUBERT A V, KONOVALOV S V, GUDALA S, et al. Modern methods of applying ceramic coatings to titanium alloys: Prospects and technological solutions[J]. Non-ferrous Metals, 2025(2): 24-35.
WANG D, LIU Z Y, DENG G W, et al. A laser powder bed fusion-based methodology for repairing damaged nickel-based turbine blades: Investigation of interfacial characteristics and hot isostatic pressing treatment[J]. Materials Characterization, 2024, 212: 113948.
SIKAN F, WANJARA P, ATABAY S E, et al. Evaluation of electron beam wire-fed deposition technology for titanium compressor blade repair[J]. Materials Today Communications, 2023, 35: 105701.
WANG Z, LI L Y, SONG Y L, et al. Microstructure and mechanical properties of TC6 blade partspan shroud repaired by directed energy deposition[J]. Surface and Coatings Technology, 2025, 513: 132516.
张学军.焊接技术在航空部件修复中的应用[J].航空维修与工程，2014(5): 47-48.
ZHANG Xuejun. Application of welding technique in aircraft component maintenance[J]. Aviation Maintenance & Engineering, 2014(5):47-48.
杨微.现代航空发动机整体叶盘的先进修复技术[J].应用激光，2011, 31(4):299-302.
YANG Wei. Advanced repair technologies of modern aero engine blisks[J]. Applied Laser, 2011, 31(4): 299-302.
卓义民，陈远航，杨春利.航空发动机叶片焊接修复技术的研究现状及展望[J].航空制造技术，2021, 64(8): 22-28.
ZHUO Yimin, CHEN Yuanhang, YANG Chunli. Research status and prospect of welding repair technology for aero-engine blades[J]. Aeronautical Manufacturing Technology, 2021, 64(8): 22-28.
ÜNAL-SAEWE T, GAHN L, KITTEL J, et al. Process development for tip repair of complex shaped turbine blades with IN718[J]. Procedia Manufacturing, 2020, 47: 1050 - 1057.
PENARANDA X, MORALEJO S, LAMIKIZ A, et al. An adaptive laser cladding methodology for blade tip repair[J]. The International Journal of Advanced Manufacturing Technology, 2017, 92(9-12): 4337-4343.
BI G J, GASSER A. Restoration of nickel-base turbine blade knife-edges with controlled laser aided additive manufacturing[J]. Physics Procedia, 2011, 12: 402-409.
姚希珍，胡泽.钛合金整体叶盘线性摩擦焊技术综述[J].航空制造技术，2011, 54(16): 43-47.
YAO Xizhen, HU Ze. Linear friction welding technology for titanium alloy disc[J]. Aeronautical Manufacturing Technology, 2011, 54(16): 43-47.
PANG X T, YAO C W, XIONG Z H, et al. Comparative study of coatings with different molybdenum equivalent on titanium alloy forged plate for laser cladding: Microstructure and mechanical properties[J]. Surface and Coatings Technology, 2022, 446: 128760.
ZHAO Z, CHEN J, TAN H, et al. Microstructure and mechanical properties of laser repaired TC4 titanium alloy[J]. Rare Metal Materials and Engineering, 2017, 46(7): 1792-1797.
MATEO A. Blisk fabrication by linear friction welding[M]//Advances in Gas Turbine Technology. Rijeka: InTech, 2011.
MATEO A. Sobre la viabilidad de los blisk producidos mediante soldadura por fricción lineal[J]. Revista de Metalurgia, 2014, 50(3): e023.
WANG Q, SHI J M, ZHANG L X, et al. Impacts of laser cladding residual stress and material properties of functionally graded layers on titanium alloy sheet[J]. Additive Manufacturing, 2020, 35: 101303.
GUO Z G, MA T J, YANG X W, et al. Comprehensive investigation on linear friction welding a dissimilar material joint between Ti17 (α+β) and Ti17 (β): Microstructure evolution, failure mechanisms, with simultaneous optimization of tensile and fatigue properties[J]. Materials Science and Engineering: A, 2024, 909:146818.
SALERNO G, BENNETT C J, SUN W, et al. Residual stress analysis and finite element modelling of repair-welded titanium sheets[J]. Welding in the World, 2017, 61(6): 1211-1223.
JAMES M N, HATTINGH D G, ASQUITH D, et al. Applications of residual stress in combatting fatigue and fracture[J]. Procedia Structural Integrity, 2016, 2: 11-25.
SAVIO E, DE CHIFFRE L. An artefact for traceable freeform measurements on coordinate measuring machines[J]. Precision Engineering, 2002, 26(1): 58-68.
FAN L S, YANG G, ZHANG Y, et al. A novel tolerance optimization approach for compressor blades: Incorporating the measured out-of-tolerance error data and aerodynamic performance[J]. Aerospace Science and Technology, 2025, 158: 109920.
JU Y P, LIU Y M, JIANG W, et al. Aerodynamic analysis and design optimization of a centrifugal compressor impeller considering realistic manufacturing uncertainties[J]. Aerospace Science and Technology, 2021, 115: 106787.
BROWN G M. Overview of threedimensional shape measurement using optical methods[J]. Optical Engineering, 2000, 39(1): 10.
BROWN M Z, BURSCHKA D, HAGER G D. Advances in computational stereo[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2003, 25(8): 993-1008.
SALVI J, PAGÈS J, BATLLE J. Pattern codification strategies in structured light systems[J]. Pattern Recognition, 2004, 37(4): 827-849.
GHORBANI H, KHAMENEIFAR F. Airfoil profile reconstruction from unorganized noisy point cloud data[J]. Journal of Computational Design and Engineering, 2021, 8(2): 740-755.
TIAN D Z, WU H, ZHANG Y, et al. An optimal reference iteration-based surface reconstruction framework for robotic grinding of additively repaired blade with local deformation[J]. Robotics and Computer-Integrated Manufacturing, 2024, 88: 102737.
GHORBANI H, KHAMENEIFAR F. Construction of damage-free digital twin of damaged aero-engine blades for repair volume generation in remanufacturing[J]. Robotics and Computer-Integrated Manufacturing, 2022, 77:102335.
CUI K, JIANG R S, JING L. Model reconstruction for worn blades based on hybrid surface registrations[J]. Advances in Manufacturing, 2022, 10(3): 479-494.
XIAO G J, HUANG Y. Surface reconstruction of laser-cladding remanufacturing blade using in adaptive belt grinding[J]. The International Journal of Advanced Manufacturing Technology, 2019, 101(9-12): 3199-3211.
GAO J, CHEN X, YILMAZ O, et al. An integrated adaptive repair solution for complex aerospace components through geometry reconstruction[J]. The International Journal of Advanced Manufacturing Technology, 2008, 36(11-12): 1170-1179.
WILSON J M, PIYA C, SHIN Y C, et al. Remanufacturing of turbine blades by laser direct deposition with its energy and environmental impact analysis[J]. Journal of Cleaner Production, 2014, 80: 170-178.
WU J, LI Z, ZHANG J, et al. Adaptive positioning repair method for aero-engine blades by using speckle vision measurement[J]. IEEE Access, 2020, 8: 73307-73319.
HE J J, LI L Y, LI J H. Research of key-technique on automatic repair system of plane blade welding[C]//2011 International Conference on Control, Automation and Systems Engineering (CASE). Piscataway, NJ: IEEE, 2011: 1- 4.
BAGCI E. Reverse engineering applications for recovery of broken or worn parts and re-manufacturing: Three case studies[J]. Advances in Engineering Software, 2009, 40(6):407-418.
JING L M, WANG H, WANG L W. 3D model reconstruction of the broken aeroengine blade based on the detection operator[J]. Applied Mechanics and Materials, 2012, 159: 1-5.
YILMAZ O, GINDY N, GAO J. A repair and overhaul methodology for aeroengine components[J]. Robotics and Computer-Integrated Manufacturing, 2010, 26(2): 190-201.
LI J H, YAO F P, LIU Y X, et al. Reconstruction of broken blade geometry model based on reverse engineering[C]//2010 Third International Conference on Intelligent Networks and Intelligent Systems. Piscataway, NJ: IEEE, 2010: 680-682.
WU B H, ZHENG H, ZHANG Y, et al. A model reconstruction method of blade repair based on linear combination[J]. International Journal of Precision Engineering and Manufacturing, 2021, 22(3): 383-394.
LI L L, LI C B, TANG Y, et al. An integrated approach of reverse engineering aided remanufacturing process for worn components[J]. Robotics and Computer-Integrated Manufacturing, 2017, 48: 39-50.
ZHANG X C, LI W, CUI W Y,et al. Modeling of worn surface geometry for engine blade repair using laser-aided direct metal deposition process[J]. Manufacturing Letters, 2018, 15: 1-4.
MOHAGHEGH K, SADEGHI M H, ABDULLAH A, et al. Improvement of reverseengineered turbine blades using construction geometry[J]. The International Journal of Advanced Manufacturing Technology, 2010, 49(5-8): 675-687.
ZHANG D H, ZHANG Y, WU B H. Research on the adaptive machining technology of blisk[J]. Advanced Materials Research, 2009, 69-70: 446-450.
YAN C Y, WAN W Q, HUANG K T, et al. A reconstruction strategy based on CSC registration for turbine blades repairing[J]. Robotics and Computer-Integrated Manufacturing, 2020, 61: 101835.
RONG Y, XU J T, SUN Y W. A surface reconstruction strategy based on deformable template for repairing damaged turbine blades[J]. Proceedings of the Institution of Mechanical Engineers, Part G:Journal of Aerospace Engineering, 2014, 228(12):2358-2370.
LI Y Q, NI J. Constraints based nonrigid registration for 2D blade profile reconstruction in reverse engineering[J]. Journal of Computing and Information Science in Engineering, 2009, 9(3):031005.
ZHAO Z C, FU Y C, LIU X, et al. Measurement-based geometric reconstruction for milling turbine blade using free-form deformation[J]. Measurement, 2017, 101: 19-27.
TSONG-JYE NG B, LIN W J, CHEN X Q, et al. Intelligent system for turbine blade overhaul using robust profile re-construction algorithm[C]//ICARCV 2004 8th Control, Automation, Robotics and Vision Conference, 2004. Kunming, 2004.
WU B H, WANG J, ZHANG Y, et al. Adaptive location of repaired blade for multi-axis milling[J]. Journal of Computational Design and Engineering, 2015, 2(4): 261-267.
ZHANG Y, CHEN Z T, NING T. Reverse modeling strategy of aero-engine blade based on design intent[J]. The International Journal of Advanced Manufacturing Technology, 2015, 81(9-12): 1781-1796.
吕学庚.航空发动机叶片流曲面重构及修复方法研究[D].哈尔滨： 哈尔滨工业大学，2019: 55-64.
LÜ Xuegeng. Research on reconstruction and repair methods of aeroengine blade stream surface[D]. Harbin: Harbin Institute of Technology, 2019: 55-64.
GUO Y M, REN J X, LIANG Y S. Aerodynamic performance-preserving construction method for a near-net-shape blade cross section[J]. Aerospace Science and Technology, 2023, 138:108313.
LI L, ZHANG X C, PAN T, et al. Component repair using additive manufacturing:Experiments and thermal modeling[J]. The International Journal of Advanced Manufacturing Technology, 2022, 119(1-2): 719-732.
YU B L, WANG P, LIU Y, et al. Residual stress distribution and deformation in wire+ arc additive manufactured titanium alloy: Insights from simulation and cold cutting analysis[J]. Welding in the World, 2025, 69(6): 1563-1579.
SU J H, CAI Y, JIANG X H, et al. Modeling of stiffness characteristic on evaluating clamping scheme of milling of thin-walled parts[J]. The International Journal of Advanced Manufacturing Technology, 2021, 113(7-8):1861-1872.
ZHENG Y, WU D B, WANG H, et al. Machining fixture and deformation control of aeroengine thin-walled casing[J]. The International Journal of Advanced Manufacturing Technology, 2023, 129(11-12): 5601-5614.
ZHOU Y, JIANG Y M, LU C, et al. A review of 5-axis milling techniques for centrifugal impellers: Tool-path generation and deformation control[J]. Journal of Manufacturing Processes, 2024, 131: 160-186.
SUN H C, ZHAO J C, ZHENG Z P, et al. A review of the deformation mechanism and control of low stiffness thin-walled parts[J]. CIRP Journal of Manufacturing Science and Technology, 2025, 60: 322-355.
LI W T, WANG L P, YU G. Chatter prediction in flank milling of thin-walled parts considering force-induced deformation[J]. Mechanical Systems and Signal Processing, 2022, 165: 108314.
LIN M H, WANG C H, YUE T, et al. Deformation prediction in flank milling of thin-walled parts based on cutter-workpiece engagement[J]. Journal of Manufacturing Processes, 2024, 115:375-386.
岳彩旭，张俊涛，刘献礼，等.薄壁件铣削过程加工变形研究进展[J].航空学报，2022, 43(4): 99-124.
YUE Caixu, ZHANG Juntao, LIU Xianli, et al. Research progress on machining deformation of thin-walled parts in milling process[J]. Acta Aeronautica et Astronautica Sinica, 2022, 43(4):99-124.
KLINE W A, DEVOR R E, SHAREEF I A. The prediction of surface accuracy in end milling[J]. Journal of Engineering for Industry, 1982, 104(3): 272-278.
SUTHERLAND J W, DEVOR R E. An improved method for cutting force and surface error prediction in flexible end milling systems[J]. Journal of Engineering for Industry, 1986, 108(4):269-279.
BUDAK E, ALTINTAS Y. Modeling and avoidance of static form errors in peripheral milling of plates[J]. International Journal of Machine Tools and Manufacture, 1995, 35(3):459-476.
ALTINTAS Y, MONTGOMERY D, BUDAK E. Dynamic peripheral milling of flexible structures[J]. Journal of Engineering for Industry, 1992, 114(2): 137-145.
KANG Y G, WANG Z Q. Two efficient iterative algorithms for error prediction in peripheral milling of thin-walled workpieces considering the in-cutting chip[J]. International Journal of Machine Tools and Manufacture, 2013, 73: 55-61.
JIA Z Y, LU X H, GU H, et al. Deflection prediction of micro-milling Inconel 718 thin-walled parts[J]. Journal of Materials Processing Technology, 2021, 291: 117003.
TSAI J S, LIAO C L. Finite-element modeling of static surface errors in the peripheral milling of thin-walled workpieces[J]. Journal of Materials Processing Technology, 1999, 94(2-3):235-246.
RAI J K, XIROUCHAKIS P. Finite element method based machining simulation environment for analyzing part errors induced during milling of thin-walled components[J]. International Journal of Machine Tools and Manufacture, 2008, 48(6): 629-643.
WANG L P, SI H. Machining deformation prediction of thin-walled workpieces in five-axis flank milling[J]. The International Journal of Advanced Manufacturing Technology, 2018, 97(9-12): 4179-4193.
HE N, WANG Z G, JIANG C Y, et al. Finite element method analysis and control stratagem for machining deformation of thinwalled components[J]. Journal of Materials Processing Technology, 2003, 139(1-3): 332-336.
LIU S M, SHAO X D, GE X B, et al. Simulation of the deformation caused by the machining cutting force on thin-walled deep cavity parts[J]. The International Journal of Advanced Manufacturing Technology, 2017, 92(9-12):3503-3517.
RATCHEV S, LIU S, HUANG W, et al. Milling error prediction and compensation in machining of low-rigidity parts[J]. International Journal of Machine Tools and Manufacture, 2004, 44(15): 1629-1641.
RATCHEV S, LIU S L, HUANG W, et al. Machining simulation and system integration combining FE analysis and cutting mechanics modelling[J]. The International Journal of Advanced Manufacturing Technology, 2007, 35(1-2): 55-65.
LI X, GONG Y D, DING M X, et al. Research on prediction and compensation strategy of milling deformation error of aitanium alloy integral blisk blade[J]. The International Journal of Advanced Manufacturing Technology, 2023, 127(11-12): 5099-5117.
LI Z L, TUYSUZ O, ZHU L M, et al. Surface form error prediction in five-axis flank milling of thin-walled parts[J]. International Journal of Machine Tools and Manufacture, 2018, 128: 21-32.
HUANG W W, ZHANG Y, ZHANG X Q, et al. Wall thickness error prediction and compensation in end milling of thin-plate parts[J]. Precision Engineering, 2020, 66: 550-563.
WAN M, ZHANG W H. Efficient algorithms for calculations of static form errors in peripheral milling[J]. Journal of Materials Processing Technology, 2006, 171(1): 156-165.
WEI P X, WANG L P, LI W T. A deformation prediction method for thin-walled workpiece machining based on the voxel octree model[J]. Machines, 2025, 13(9): 803.
WAN M, ZHANG W H, QIU K P, et al. Numerical prediction of static form errors in peripheral milling of thin-walled workpieces with irregular meshes[J]. Journal of Manufacturing Science and Engineering, 2005, 127(1): 13-22.
TUYSUZ O, ALTINTAS Y. Frequency domain updating of thin-walled workpiece dynamics using reduced order substructuring method in machining[J]. Journal of Manufacturing Science and Engineering, 2017, 139(7): 071013.
LI W T, WANG L P, YU G. Forceinduced deformation prediction and flexible error compensation strategy in flank milling of thinwalled parts[J]. Journal of Materials Processing Technology, 2021, 297: 117258.
GE G Y, XIAO Y K, FENG X B, et al. An efficient prediction method for the dynamic deformation of thin-walled parts in flank milling[J]. Computer-Aided Design, 2022, 152:103401.
TANG Y R, GAO F, LI Y, et al. Based on CWE-driven and two-stage static condensation: A force-induced deformation model for flank milling of thin-walled parts[J]. Journal of Manufacturing Processes, 2025, 152: 308-331.
WANG M H, SUN Y. Error prediction and compensation based on interference-free tool paths in blade milling[J]. The International Journal of Advanced Manufacturing Technology, 2014, 71(5-8): 1309-1318.
ALTINTAS Y, TUYSUZ O, HABIBI M, et al. Virtual compensation of deflection errors in ball end milling of flexible blades[J]. CIRP Annals, 2018, 67(1): 365-368.
马伟.航空铝合金薄壁件切削过程及加工变形仿真分析[D].长春： 吉林大学，2020: 35-52.
MA Wei. Simulation analysis of cutting process and machining deformation of aviation aluminum alloy thin-walled parts[D]. Changchun:Jilin University, 2020: 35-52.
郭建烨，郑若池.基于改进烟花算法的薄壁件铣削加工参数优化[J].制造技术与机床，2021(6): 70-74, 80.
GUO Jianye, ZHENG Ruochi. Optimization of milling parameters of thin-walled parts based on improved firework algorithm[J]. Manufacturing Technology & Machine Tool, 2021(6): 70-74, 80.
LIU F, ZHANG N S, WANG A M, et al. Deformation prediction of thin-walled parts based on BP neural network[C]//2021 2nd International Symposium on Computer Engineering and Intelligent Communications (ISCEIC). Nanjing, 2021.
YU Y Y, SHI D M, DING H, et al. Prediction of thin-walled workpiece machining error: A transfer learning approach[J]. Journal of Intelligent Manufacturing, 2025, 36(4): 2803-2827.
张思琪.数据驱动的薄壁叶片加工变形预测方法研究[D].西安： 西北工业大学，2023: 57-71.
ZHANG Siqi. Research on data-driven prediction method of machining deformation for thin-walled blades[D]. Xi'an: Northwestern Polytechnical University, 2023: 57-71.
董立卓，张思琪，张钊，等.机理-数据混合驱动的叶片加工变形预测方法[J].航空学报，2024, 45(13): 629037.
DONG Lizhuo, ZHANG Siqi, ZHANG Zhao, et al. Prediction method of blade machining deformation driven by mechanism-data hybrid[J].Acta Aeronautica et Astronautica Sinica, 2024, 45(13): 629037.
CAO L, ZHANG X M, HUANG T, et al. Online monitoring machining errors of thinwalled workpiece: A knowledge embedded sparse Bayesian regression approach[J]. IEEE/ASME Transactions on Mechatronics, 2019, 24(3): 1259-1270.
LI J J, ZHOU G H, ZHANG C, et al. An online milling deformation prediction method for thin-walled features with domain adversarial neural networks under small samples[J]. Computers in Industry, 2025, 172: 104349.
LI Z L, ZHU L M. Compensation of deformation errors in five-axis flank milling of thin-walled parts via tool path optimization[J]. Precision Engineering, 2019, 55: 77-87.
RATCHEV S, LIU S, BECKER A A. Error compensation strategy in milling flexible thin-wall parts[J]. Journal of Materials Processing Technology, 2005, 162: 673-681.
DU Z C, ZHANG D, HOU H F, et al. Peripheral milling force induced error compensation using analytical force model and APDL deformation calculation[J]. The International Journal of Advanced Manufacturing Technology, 2017, 88(9-12): 3405-3417.
WU D B, WANG H, YU J. Research on machining error transmission mechanism and compensation method for near-net-shaped jet engine blades CNC machining process[J]. The International Journal of Advanced Manufacturing Technology, 2021, 117(9-10): 2755-2773.
CHEN W F, XUE J B, TANG D B, et al. Deformation prediction and error compensation in multilayer milling processes for thin-walled parts[J]. International Journal of Machine Tools and Manufacture, 2009, 49(11): 859-864.
SI H, WANG L P. Error compensation in the five-axis flank milling of thin-walled workpieces[J]. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 2019, 233(4): 1224-1234.
WANG L P, LI W T, YU G. Optimal deformation error compensation process in flank milling of thin-walled workpieces[J]. The International Journal of Advanced Manufacturing Technology, 2023, 126(9-10): 4353-4367.
WAN M, ZHANG W H, QIN G H, et al. Strategies for error prediction and error control in peripheral milling of thin-walled workpiece[J]. International Journal of Machine Tools and Manufacture, 2008, 48(12-13): 1366-1374.
SUH S H, CHO J H, HASCOET J Y. Incorporation of tool deflection in tool path computation: Simulation and analysis[J]. Journal of Manufacturing Systems, 1996, 15(3): 190-199.
MA W K, HE G Y, ZHU L M, et al. Tool deflection error compensation in fiveaxis ball-end milling of sculptured surface[J]. The International Journal of Advanced Manufacturing Technology, 2015, 84: 1421-1430.
HABIBI M, AREZOO B, VAHEBI NOJEDEH M. Tool deflection and geometrical error compensation by tool path modification[J]. International Journal of Machine Tools and Manufacture, 2011, 51(6): 439-449.
莫翔.基于在机检测的叶片加工误差补偿技术研究[D].北京： 北京交通大学，2016: 55-76.
MO Xiang. The reaserch on error compensation technique for blade machining based on the on-machine measurement[D]. Beijing:Beijing Jiaotong University, 2016: 55-76.
陈岳坪，高健，邓海祥，等.复杂曲面零件在线检测与误差补偿方法[J].机械工程学报，2012, 48(23): 143-151.
CHEN Yueping, GAO Jian, DENG Haixiang, et al. On-line inspection and machining error compensation for complex surfaces[J]. Journal of Mechanical Engineering, 2012, 48(23): 143-151.
GUIASSA R, MAYER J R R. Predictive compliance based model for compensation in multi-pass milling by on-machine probing[J]. CIRP Annals, 2011, 60(1): 391-394.
GUIASSA R, MAYER J R R, BALAZINSKI M, et al. Closed door machining error compensation of complex surfaces using the cutting compliance coefficient and on-machine measurement for a milling process[J]. International Journal of Computer Integrated Manufacturing, 2014, 27(11): 1022-1030.
GE G Y, DU Z C, YANG J G. Rapid prediction and compensation method of cutting force-induced error for thin-walled workpiece[J]. The International Journal of Advanced Manufacturing Technology, 2020, 106(11-12):5453-5462.
WANG X Z, LI Z L, BI Q Z, et al. An accelerated convergence approach for realtime deformation compensation in large thinwalled parts machining[J]. International Journal of Machine Tools and Manufacture, 2019, 142:98-106.
郝炜，蔺小军，单晨伟，等.薄壁叶片前后缘加工误差补偿技术研究[J].机械科学与技术，2011, 30(9): 1446-1450.
HAO Wei, LIN Xiaojun, SHAN Chenwei, et al. Research on the machining error compensation for the leading and trailing edges of thin-walled blades[J]. Mechanical Science and Technology, 2011, 30(9): 1446-1450.
丛靖梅，莫蓉，张莹，等.航空发动机薄壁叶片加工误差补偿迭代学习建模方法[J].机械科学与技术，2019, 38(1): 73-79.
CONG Jingmei, MO Rong, ZHANG Ying, et al. Iterative learning modeling method of error compensation for machining of aeroengine thinwall blade[J]. Mechanical Science and Technology for Aerospace Engineering, 2019, 38(1): 73-79.
LIM E M, MENQ C H. Error compensation for sculptured surface productions by the application of control-surface strategy using predicted machining errors[J]. Journal of Manufacturing Science and Engineering, 1997, 119(3): 402-409.
CHO M W, SEO T I. Machining error compensation using radial basis function network based on CAD/CAM/CAI integration concept[J]. International Journal of Production Research, 2002, 40(9): 2159-2174.
侯尧华.薄壁叶片精密加工余量与误差的动态建模与学习控制方法[D].西安：西北工业大学，2021: 93-120.
HOU Yaohua. The dynamic modeling and learning control method of the allowance and error in the precision machining of thin-walled blade[D]. Xi'an: Northwestern Polytechnical University, 2021: 93-120.
HUANG Y M, ZHU L D, HAO Y P, et al. Error compensation for thin-walled blade machining based on analytical modeling and ensemble machine learning[J]. Thin-Walled Structures, 2026, 219: 114285.
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