CIRP Journal of Manufacturing Science and Technology最新文献_第6页

Cutter design and generating process for tooth profile chamfering of involute cylindrical gears with cylindrical tools 用圆柱刀具进行渐开线圆柱齿轮齿廓倒角的刀具设计及加工工艺

IF 5.4 2区工程技术 Q2 ENGINEERING, MANUFACTURING

CIRP Journal of Manufacturing Science and Technology

Pub Date : 2025-12-01 Epub Date: 2025-10-14 DOI: 10.1016/j.cirpj.2025.09.019

Qi Dong, Yuwen Sun

Gear tooth profile chamfering plays a crucial role in mitigating stress concentration and reducing meshing impact. However, chamfer grinding and radial chamfering are inefficient because the tools for both methods work individually along the end face profile. Additionally, resharpening error occurs in the chamfer hobbing method because the contour of conical chamfer hobbing tool changes after resharpening. Considering that cylindrical tools enable continuous cutting at high speeds by engaging with the gear to be chamfered and maintains a constant cross-sectional profile, this study proposes a tooth profile chamfering method of involute cylindrical gears with cylindrical tools. Firstly, a basic mathematical model of tooth profile chamfering using a cylindrical tool is established, including the geometrical model of the chamfered surface and the machine configuration. Subsequently, the rake faces and cutting edges of the cylindrical tools for gear tooth profile chamfering are calculated based on the conjugate principle. Then, the interference during the chamfering process is checked and the chamfered surfaces are generated using the calculated cylindrical tools. In addition, the chamfer structures of the left and right profiles are machined individually, which helps to achieve uniform distributed tooth profile chamfered surfaces. As demonstrated by simulation and experimental verification, the proposed method using cylindrical tools is feasible and meets the requirements of tooth profile chamfering.

齿轮齿形倒角在减轻应力集中和减小啮合冲击方面起着至关重要的作用。然而，倒角磨削和径向倒角是低效的，因为这两种方法的工具都是沿着端面轮廓单独工作的。另外，由于锥形倒角滚刀刀具的轮廓在重新锐化后发生了变化，因此在倒角滚刀方法中会产生再锐化误差。考虑到圆柱刀具通过与待倒角齿轮啮合，实现高速连续切削，并保持截面轮廓不变的特点，提出了用圆柱刀具对渐开线圆柱齿轮进行齿形倒角的方法。首先，建立了圆柱刀具齿形倒角的基本数学模型，包括倒角面几何模型和机床结构；然后，基于共轭原理，计算了齿轮齿形倒角圆柱刀具的前刀面和切削刃。然后，对倒角过程中的干涉进行校核，并利用计算得到的圆柱刀具生成倒角曲面。另外，对左右齿形的倒角结构进行单独加工，使齿形倒角表面分布均匀。仿真和实验验证表明，采用圆柱刀具进行齿形倒角是可行的，满足齿形倒角的要求。

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引用次数: 0

Comprehensive study of grinding burn limit and subsurface modifications in grinding with CBN and corundum abrasives CBN和刚玉磨料磨削燃烧极限和亚表面改性的综合研究

IF 5.4 2区工程技术 Q2 ENGINEERING, MANUFACTURING

CIRP Journal of Manufacturing Science and Technology

Pub Date : 2025-12-01 Epub Date: 2025-11-08 DOI: 10.1016/j.cirpj.2025.11.001

Gerrit Kuhlmann , Nikolai Guba , Tobias Hüsemann , Carsten Heinzel

This study investigates the shift in the thermal process limit for CBN compared to corundum abrasives as a function of specific grinding power and contact time during surface and cylindrical grinding. The results indicate that the use of CBN significantly reduces the thermal load, as demonstrated by metallographic cross-sections, residual stress depth profiles and hardness measurements. An empirical function is derived to calculate the depth of tempering zones. This enables a quantifiable comparison of CBN and corundum in terms of their thermal impact and provides a practical basis for the targeted and thermally stable design of multi-stage grinding processes.

本研究考察了CBN磨料与刚玉磨料相比，其热过程极限随磨削功率和接触时间的变化。结果表明，金相截面、残余应力深度分布和硬度测量表明，CBN的使用显著降低了热负荷。导出了一个计算回火区深度的经验函数。这使得CBN和刚玉在热影响方面的可量化比较成为可能，并为多阶段磨削工艺的针对性和热稳定性设计提供了实践依据。

引用次数: 0

Fatigue failure mechanism of gradient nanostructured materials produced by turning 车削梯度纳米结构材料疲劳失效机理研究

IF 5.4 2区工程技术 Q2 ENGINEERING, MANUFACTURING

CIRP Journal of Manufacturing Science and Technology

Pub Date : 2025-12-01 Epub Date: 2025-09-23 DOI: 10.1016/j.cirpj.2025.09.013

Lihua He, Jinhui Zhou, Bokai Lou, Jing Ni, Xiaoping Hu

Most safety-critical components and load-bearing structures continue to be manufactured using hard turning, a process that induces gradient nanostructures (GNS) in the surface layer. To investigate the effect of GNS layer on fatigue properties, crystal plasticity finite element model (CPFEM) and ± 0.8 % strain fatigue test were used in this study. The objectives were to investigate the correlation between turning parameters and surface GNS layer of 316 L stainless steel, and to reveal the fatigue failure mechanism of GNS layer from multiple scales. The results show that the turning parameters significantly influence the thickness of the GNS layer, with turning depth having the greatest impact, followed by cutting speed. CPFEM simulations predict stress distribution within the GNS layer across regions with varying grain sizes. stresses in fine-grained regions are primarily concentrated at grain boundaries, whereas stresses in coarse-grained regions are distributed within the grains. The model predictions of fatigue crack locations closely align with stress concentration distributions. Fatigue testing reveals that cracks in the GNS layer primarily propagate intergranular boundaries, while cracks in the coarse-grained (CG) layer exhibit both intergranular and transgranular extensions. This behavior mirrors the damage patterns predicted by simulation, demonstrating the model's high accuracy.

大多数安全关键部件和承重结构继续使用硬车削制造，这是一种在表层诱导梯度纳米结构（GNS）的工艺。为了研究GNS层对疲劳性能的影响，采用晶体塑性有限元模型（CPFEM）和±0.8 %应变疲劳试验。研究316 L不锈钢车削参数与表面GNS层的关系，从多个尺度揭示GNS层的疲劳破坏机理。结果表明：车削参数对GNS层厚度影响显著，其中车削深度影响最大，其次是切削速度；CPFEM模拟预测了GNS层内不同晶粒尺寸区域的应力分布。细晶区的应力主要集中在晶界处，而粗晶区的应力主要分布在晶粒内。模型预测的疲劳裂纹位置与应力集中分布密切相关。疲劳试验表明，GNS层的裂纹主要沿晶扩展，而粗晶（CG）层的裂纹同时沿晶扩展和穿晶扩展。这种行为反映了模拟预测的损伤模式，证明了模型的高准确性。

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引用次数: 0

Hybrid neural network framework for predicting tool tip dynamics via receptance coupling 基于接收耦合预测刀尖动态的混合神经网络框架

IF 5.4 2区工程技术 Q2 ENGINEERING, MANUFACTURING

CIRP Journal of Manufacturing Science and Technology

Pub Date : 2025-12-01 Epub Date: 2025-11-19 DOI: 10.1016/j.cirpj.2025.11.006

Peiyuan Su , Chung-Yu Tai, Yusuf Altintas

Tool tip frequency response functions (FRFs) are fundamental to predicting stability lobe diagrams and mitigating chatter in machining operations. This study introduces a hybrid framework that integrates physics-based modeling with data-driven learning to reduce approximation errors in tool holder–tool geometries and mitigate uncertainties in their contact parameters. The tools and tool holders are modeled using a Timoshenko beam-based finite element formulation and assembled as free-free structures via receptance coupling substructure analysis (RCSA). Uncertainties in the elastic modulus, Poisson’s ratio, and density of the tool and holder materials are minimized by aligning the measured and simulated natural frequencies of representative tool and holder samples. Neural network models are pre-trained using simulated FRFs with approximate contact parameters and subsequently fine-tuned through a limited number of experimental free-free impact tests on holder–tool assemblies. The optimized contact parameters are then archived in the database for each holder type. The finite element models of the tools and holders are coupled using the tuned contact parameters and subsequently assembled with the stored spindle model via RCSA. The proposed hybrid approach is experimentally validated through impact testing of diverse holder–tool configurations mounted on machine tools. The resulting methodology contributes to the establishment of a robust digital machine tool database, thereby facilitating more reliable stability predictions and enabling enhanced productivity in NC part programming within CAM systems.

刀尖频响函数（frf）是预测加工过程中稳定性波瓣图和减少颤振的基础。该研究引入了一种混合框架，将基于物理的建模与数据驱动的学习相结合，以减少刀柄-刀具几何形状的近似误差，并减轻其接触参数的不确定性。刀具和刀架采用基于Timoshenko梁的有限元公式建模，并通过接受耦合子结构分析（RCSA）将其组装为自由-自由结构。通过校准代表性工具和刀柄样本的测量和模拟固有频率，工具和刀柄材料的弹性模量、泊松比和密度的不确定性最小化。神经网络模型使用模拟的frf进行预训练，并带有近似的接触参数，随后通过有限数量的刀柄-工具组件自由冲击试验进行微调。然后将优化后的接触参数存档到数据库中，用于每种持刀类型。刀具和刀架的有限元模型使用调整后的接触参数进行耦合，然后通过RCSA与存储的主轴模型进行组装。通过在机床上安装不同刀柄-刀具结构的冲击试验验证了所提出的混合方法。由此产生的方法有助于建立一个强大的数字机床数据库，从而促进更可靠的稳定性预测，并在CAM系统内提高数控零件编程的生产率。

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引用次数: 0

A machining accuracy enhancement strategy for large composite components with edge milling robots 一种利用刃铣机器人提高大型复合材料零件加工精度的策略

IF 5.4 2区工程技术 Q2 ENGINEERING, MANUFACTURING

CIRP Journal of Manufacturing Science and Technology

Pub Date : 2025-12-01 Epub Date: 2025-10-29 DOI: 10.1016/j.cirpj.2025.10.007

Qi Zhang , Pengcheng Li , Mingyu Li , Wei Tian , Pinzhang Wang

Due to deformation in large composite components and trajectory errors in industrial robots, it is difficult to meet the machining accuracy requirements for large composite components processed by edge milling robots. To address this issue, a strategy for enhancing the machining accuracy of large composite components based on a line laser profilometer and a binocular vision tracking system is proposed. To accurately extract the center of scale lines, a sliding window and model matching (SW-MM) extraction method is designed. A combined weighted random sampling consistency and least squares (WRANSAC-LS) method is developed for normal estimation to mitigate the impact of surface curvature and measurement noise on estimation accuracy. Subsequently, in terms of visual servo control, an adaptive sliding mode controller (ASMC) is designed to further enhance the trajectory accuracy of the milling robot. Finally, a series of validation experiments is conducted on the designed milling robot system platform. Experimental results demonstrate that the strategy proposed in this paper reduces machining errors in large composite components to ±0.2 mm, achieving a 90 % improvement in precision, meeting the machining precision requirements for composite components in the aerospace industry.

由于大型复合部件的变形和工业机器人的轨迹误差，使得铣削机器人加工大型复合部件的加工精度难以满足要求。针对这一问题，提出了一种基于直线激光轮廓仪和双目视觉跟踪系统的大型复合材料零件加工精度提高策略。为了准确提取比例线中心，设计了滑动窗口和模型匹配（SW-MM）提取方法。为了消除表面曲率和测量噪声对正态估计精度的影响，提出了加权随机抽样一致性和最小二乘（WRANSAC-LS）组合方法。随后，在视觉伺服控制方面，设计了自适应滑模控制器（ASMC），进一步提高铣削机器人的轨迹精度。最后，在设计的铣削机器人系统平台上进行了一系列验证实验。实验结果表明，本文提出的策略将大型复合材料部件的加工误差减小到±0.2 mm，精度提高了90 %，满足了航空航天工业对复合材料部件的加工精度要求。

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引用次数: 0

Influence mechanism of tool pin profile on heat transfer and material flow behavior in friction stir welding of aluminum alloys 刀具销型对铝合金搅拌摩擦焊传热和材料流动行为的影响机理

IF 5.4 2区工程技术 Q2 ENGINEERING, MANUFACTURING

CIRP Journal of Manufacturing Science and Technology

Pub Date : 2025-12-01 Epub Date: 2025-10-10 DOI: 10.1016/j.cirpj.2025.10.001

Fanqi Yu, Shujun Chen, Tao Yuan, He Shan, Pengjing Zhao

The design of the tool pin is a critical factor influencing weld quality and material flow behavior in friction stir welding (FSW). This study employs a Coupled Eulerian-Lagrangian (CEL) thermo-mechanical model to systematically investigate the effects of tool pin taper angle on thermal cycles, plastic strain, and material flow during FSW of Al alloys. The model integrates interfacial friction heating, viscoplastic constitutive behavior, and thermomechanical contact conditions. Experimental validation was conducted through thermocouple-based temperature measurements and macrostructural analysis of weld cross-sections. Results indicate that larger taper angles enhance longitudinal thermal gradients and promote lateral heat dissipation, leading to a wider thermomechanically affected zone (TMAZ). A 0° taper angle induces significant adhesive friction and intense material flow, while a 60° taper reduces flow velocity near the pin tip. With increasing taper angle, plastic strain transitions from a uniform distribution to a concentrated region on the advancing side (AS) of the stir zone (SZ), where peak plasticity occurs. Conversely, deformation near the pin root is suppressed. These insights offer a theoretical basis for optimizing tool geometry to control heat distribution and material flow, improving weld quality in engineering applications.

工具销的设计是影响搅拌摩擦焊焊接质量和材料流动特性的关键因素。本研究采用欧拉-拉格朗日（CEL）耦合热力学模型，系统研究了刀具销锥角对铝合金摩擦摩擦过程中热循环、塑性应变和材料流动的影响。该模型集成了界面摩擦加热，粘塑性本构行为和热机械接触条件。通过基于热电偶的温度测量和焊缝截面的宏观结构分析进行了实验验证。结果表明，较大的锥度角增强了纵向热梯度，促进了侧向散热，导致更宽的热机械影响区（TMAZ）。当锥度为0°时，会产生明显的粘着摩擦和强烈的物质流动，而当锥度为60°时，则会降低针尖附近的流速。随着锥度角的增大，塑性应变由均匀分布向搅拌区（SZ）前进侧（AS）的集中区域转变，塑性峰值出现在搅拌区（SZ）前进侧（AS）。相反，销根附近的变形受到抑制。这些见解为优化工具几何形状以控制热分布和材料流动，提高工程应用中的焊接质量提供了理论基础。

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引用次数: 0

Thermal error prediction of CNC Swiss-type lathe under variable operating conditions based on symbolic regression and time series mixup enhancement 基于符号回归和时间序列混合增强的数控瑞士型车床变工况热误差预测

IF 5.4 2区工程技术 Q2 ENGINEERING, MANUFACTURING

CIRP Journal of Manufacturing Science and Technology

Pub Date : 2025-12-01 Epub Date: 2025-10-17 DOI: 10.1016/j.cirpj.2025.09.018

Shan Wu , Lingfei Kong , Aokun Wang , Xiaoyang Feng

Accurately predicting thermal errors is vital for developing effective strategies to compensate for them. Machine learning thermal errors models (ML-TEMs) offer significant advantages over traditional regression models. However, current ML-TEMs, such as neural networks and support vector machines, are black-box models. These models lack interpretability and are challenging to apply in engineering. Additionally, these methods depend heavily on extensive amounts of training data. The scarcity of labeled time-series data for Swiss-type lathe may hinder the model's ability to generalize across varying operating conditions. To address these issues, this paper proposes a symbolic regression model based on Time Series Mixup (TSM) enhancement. The TSM method was used to enhance the training data. The optimal interpretable model is obtained through fitness assessment and screening. The proposed model exhibits high prediction accuracy. In particular, it demonstrates superior accuracy and stability under complex operating conditions with random variations.

准确预测热误差对于制定有效的补偿策略至关重要。与传统的回归模型相比，机器学习热误差模型（ml - tem）具有显著的优势。然而，目前的ml - tem，如神经网络和支持向量机，都是黑盒模型。这些模型缺乏可解释性，在工程应用中具有挑战性。此外，这些方法严重依赖于大量的训练数据。瑞士型车床标记的时间序列数据的稀缺性可能会阻碍模型的能力，以概括不同的操作条件。针对这些问题，本文提出了一种基于时间序列混合（TSM）增强的符号回归模型。采用TSM方法对训练数据进行增强。通过适应度评估和筛选得到最优的可解释模型。该模型具有较高的预测精度。特别是，在随机变化的复杂操作条件下，它表现出优越的精度和稳定性。

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引用次数: 0

Research on the deformation mechanism for current-assisted splitting spinning forming of small-module gear-shaped parts with extreme diameter-to-module ratios 极径模比小模数齿轮件电流辅助劈裂旋压成形变形机理研究

IF 5.4 2区工程技术 Q2 ENGINEERING, MANUFACTURING

CIRP Journal of Manufacturing Science and Technology

Pub Date : 2025-12-01 Epub Date: 2025-09-18 DOI: 10.1016/j.cirpj.2025.08.012

Qinxiang Xia , Haoyang Zhou , Gangfeng Xiao , Sizhu Cheng , Junhao Zhang

Small-module gear-shaped parts (SMGSPs, module m < 1) with extreme diameter-to-module ratios (D/m>100) are critical components in miniature precision systems for spatial transmission and lightweight structural applications. However, it exhibits restricted fatigue strength and excessive material wastage when manufactured by conventional machining processes. A novel current-assisted splitting spinning forming (CASSF) method combining the precision of spinning technology with the electroplastic effects of pulsed current synergistically was proposed to realize the high-performance near-net shape forming of SMGSPs. A finite element model coupled with the electroplasticity effect is constructed. Finite element model (FEM) simulations and experimental studies systematically investigated the distribution of the electric field, temperature field, the equivalent stress and strain, and the dynamic material flow of small module gears during CASSF. The results revealed that the current density of the SMGSP is concentrated near the contact area of the roller, so the softening region, due to the electroplasticity effect, highly overlaps with the deformation region of the SMGSP. The gear profile deformation exhibits a non-uniform stress-strain distribution, with peak stress concentrations localized at the exit-side tooth root arc. The application of pulsed current effectively reduced equivalent stress and enhanced material deformability, achieving saturation thresholds at 17.5 A/mm² current density (J_p) and 40 % duty ratio (d). Five distinct material flow orientations develop during CASSF, forming four flow division surfaces between them. The uneven tooth height defect originates from asymmetric material flow between the entry and exit sides, whereas tooth underfilling stems from insufficient axial material flow. A forward-reversed forming strategy with intensified pulsed current eliminated tooth height discrepancies and improved tooth saturation (γ) to 97.8 %, demonstrating the potential of CASSF potential for forming extreme ratio SMGSPs.

具有极径模比（D/m>100）的小模块齿轮形零件（smgsp，模块m <； 1）是用于空间传动和轻量化结构应用的微型精密系统的关键部件。然而，当用传统的加工工艺制造时，它表现出有限的疲劳强度和过度的材料浪费。为了实现smgsp的高性能近净成形，提出了一种将旋压技术的精度与脉冲电流的电塑性效应协同结合的电流辅助分裂旋压成形方法。建立了考虑电塑性效应的有限元模型。通过有限元模型仿真和实验研究，系统地研究了小模数齿轮在CASSF过程中的电场、温度场、等效应力和应变分布以及动态物质流动。结果表明：SMGSP的电流密度集中在滚子接触区附近，因此由于电塑性效应，SMGSP的软化区与变形区高度重叠；齿形变形呈现非均匀应力应变分布，应力峰值集中在齿根弧出口处。脉冲电流的应用有效地降低了等效应力，增强了材料的变形能力，达到了17.5 A/mm²电流密度（Jp）和40 %占空比(d)的饱和阈值。在CASSF过程中，形成了五种不同的物质流动方向，在它们之间形成了四个流动划分面。齿高不均匀缺陷是由于进、出口侧物料流动不对称造成的，而齿深充填是由于轴向物料流动不足造成的。脉冲电流增强的正反向成形策略消除了齿高差异，并将齿饱和度（γ）提高到97.8% %，证明了CASSF潜力形成极端比smgsp的潜力。

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引用次数: 0

Modelling of abrasive particle distribution for pre-mixed abrasive water jet peening surface 预混合磨料水射流喷丸表面磨料颗粒分布建模

IF 5.4 2区工程技术 Q2 ENGINEERING, MANUFACTURING

CIRP Journal of Manufacturing Science and Technology

Pub Date : 2025-12-01 Epub Date: 2025-09-22 DOI: 10.1016/j.cirpj.2025.09.010

Zhao Wang , Xiaowen Rong , Haoran Zhao , Yue Yang , Fusheng Liang , Cheng Fan

Abrasive water jet technology, as a non-traditional machining process, impinges on the workpiece surface with abrasive particles driven by the water jet beam to achieve material removal or surface modification. The abrasive particle distribution is the key factor affecting on the process quality, especially for Abrasive Water Jet Peening (AWJP) process. However, there is still limited research on the abrasive particle distribution in the AWJP process, especially regarding the distribution under variable traverse speeds and variable curvature movements of the abrasive water jet beam, which forms the basis for controlling abrasive water jet coverage, particularly on curved surfaces. In this study, an abrasive particle distribution prediction model is proposed for AWJP under different pump pressures, variable traverse speeds (accelerations), and various curvature radius by combining finite element and analytical modeling approaches. Validation experiments were conducted, and both simulation and experimental results under different parameters follow Gaussian distributions. The maximum prediction error was only 18.6 % across 24 comparisons from 15 experimental sets, confirming the feasibility and accuracy of the proposed model. Meanwhile, the influence of these three parameters on abrasive particle distribution laws is investigated respectively through comparisons between simulation and experimental results. The findings reveal that pump pressure primarily affects abrasive particle velocity and position distribution; traverse speed mainly influences abrasive particle position distribution and the percentage of particles at the central region; curvature radius predominantly affects the midline position of the abrasive particle distribution curve. This study not only provide a deep understanding of abrasive particle distribution laws under varying pump pressures, traverse speeds, and curvature radii, but the proposed model also offers valuable guidance for achieving uniform abrasive particle coverage on free-form surfaces during AWJP.

磨料水射流技术是一种非传统的加工工艺，在水射流光束的驱动下，使磨料颗粒撞击工件表面，达到去除材料或表面改性的目的。磨料颗粒分布是影响工艺质量的关键因素，特别是磨料水喷丸工艺。然而，对AWJP过程中磨料颗粒分布的研究仍然有限，特别是对磨料水射流束在变横移速度和变曲率运动下的分布，这是控制磨料水射流覆盖范围的基础，特别是在曲面上。本文采用有限元和解析建模相结合的方法，建立了不同泵压力、变横移速度（加速度）和不同曲率半径条件下AWJP的磨粒分布预测模型。进行了验证实验，不同参数下的仿真和实验结果均服从高斯分布。在15个实验集的24个对比中，最大预测误差仅为18.6 %，证实了所提出模型的可行性和准确性。同时，通过仿真结果与实验结果的对比，研究了这三个参数对磨粒分布规律的影响。结果表明：泵压力主要影响磨粒速度和位置分布；横移速度主要影响磨料颗粒的位置分布和颗粒在中心区域的百分比；曲率半径主要影响磨粒分布曲线的中线位置。这项研究不仅提供了对不同泵压力、穿越速度和曲率半径下磨粒分布规律的深入理解，而且所提出的模型也为在AWJP过程中实现自由曲面上均匀覆盖磨粒提供了有价值的指导。

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引用次数: 0

Integration modeling of surface topography for machining ring-shaped workpiece considering multiple geometric and location error sources 考虑多种几何和位置误差源的环形工件加工表面形貌集成建模

IF 5.4 2区工程技术 Q2 ENGINEERING, MANUFACTURING

CIRP Journal of Manufacturing Science and Technology

Pub Date : 2025-12-01 Epub Date: 2025-10-30 DOI: 10.1016/j.cirpj.2025.10.008

Shun Liu , Xueming Du , Yang Xiang , Sun Jin

Circumferential topography is a key indicator of the machining quality of ring-shaped workpieces, and it is generally affected by multiple geometric and location error sources arising from the machine tool–fixture–workpiece system during the machining process. To enable effective control of surface quality under these compounded errors, an integrated 3D surface topography prediction model is formulated. In the proposed model, the combined motion errors of the workpiece and tool, the surface topography blank errors of the workpiece, and the alignment deviations in ring positioning using a quick-change clamping system are simultaneously represented within a unified framework. The effects of geometric errors in the machine tool, fixture, tool and workpiece on the machined surface topography are simulated using the equivalent error transmission chain of a multibody machining system. The topography deviations of matching features in the machining system and the workpiece alignment deviations of the clamping system are incorporated via a location deviation simulation algorithm. The circumferential surface topography is then reconstructed over the entire tool trajectory of the turning process. The simulation and experimental results indicate that the proposed model can effectively predict the 3D surface topography in auto-located turning of cylindrical thin-walled parts, which are typically affected by multiple geometric and location deviations, and offer theoretical guidance for surface topography control.

环向形貌是环形工件加工质量的关键指标，在加工过程中，环向形貌通常受到机床-夹具-工件系统产生的多种几何和位置误差源的影响。为了有效地控制这些复合误差下的表面质量，建立了一个集成的三维表面形貌预测模型。在该模型中，工件和刀具的组合运动误差、工件的表面形貌毛坯误差以及采用快换夹紧系统进行环定位时的对中偏差同时在一个统一的框架内表示。利用多体加工系统的等效误差传递链，模拟了机床、夹具、刀具和工件的几何误差对加工表面形貌的影响。通过位置偏差仿真算法将加工系统中匹配特征的形貌偏差和夹紧系统的工件对中偏差结合起来。然后在车削过程的整个刀具轨迹上重建周向表面形貌。仿真和实验结果表明，该模型能够有效地预测受多种几何和位置偏差影响的圆柱薄壁零件自动定位车削时的三维表面形貌，为表面形貌控制提供理论指导。

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引用次数: 0