Article
Engineering, Mechanical
Tengfei Yin, Suet To, Hanheng Du, Guoqing Zhang
Summary: This paper investigates the impact of wheel spindle error motion on surface generation in ultra-precision grinding. A grinding kinematics-based surface topography model and a wheel spindle dynamics model are utilized to explore the ground surface generation mechanism. The study proposes a novel method for predicting grinding mark patterns and spatial frequencies.
INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES
(2022)
Article
Computer Science, Artificial Intelligence
Jialan Liu, Chi Ma, Hongquan Gui, Shilong Wang
Summary: This study focuses on error compensation to increase the thermal stability of machine tools by analyzing the error mechanism of spindle systems and demonstrating the long-term memory characteristics of thermal errors. Utilizing VMD technology for data decomposition and optimizing neural network parameters have proven to enhance the robustness and generalization capability of the error model. Additionally, the VMD-GW-LSTM network model exhibits better predictive performance and compensation performance compared to other models.
APPLIED SOFT COMPUTING
(2021)
Review
Chemistry, Multidisciplinary
Jaroslaw Chrzanowski, Tadeusz Salacinski, Pawel Skiba
Summary: The condition of the spindle is crucial to the quality and operation of the machine tool. This paper discusses measurement methods for spindle error movements and their impact on workpiece quality, including requirements from European and American standards. The article also outlines current research directions and presents the authors' own work in this field.
APPLIED SCIENCES-BASEL
(2021)
Article
Engineering, Mechanical
Qihao Liao, Qin Yin, Luofeng Xie, Guofu Yin
Summary: In this paper, an improved exponential model for thermal error modeling of machine tools is proposed. The improved model combines the exponential model and the temperature-dependent model, and the parameters are determined using an improved fruit fly optimization algorithm. Experimental results show that the proposed model has high accuracy and strong robustness, making it suitable for thermal error modeling of machine tools under different conditions.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE
(2022)
Article
Engineering, Mechanical
Ashwani Pratap, Karali Patra
Summary: This paper presents a novel approach of fabricating micro-pool arrays on the secondary surface of PCD micro-tools to address the issue of wear debris entrapment. Experimental results show that the proposed design outperforms traditional methods in terms of cutting forces, debris disposal, surface finish, and tool utilization time.
Article
Engineering, Manufacturing
Ji Peng, Ming Yin, Li Cao, Luo-Feng Xie, Xian-Jun Wang, Guo-Fu Yin
Summary: An analytical modeling method was proposed to study the spindle angular thermal errors of a CNC machine tool. The model considered the effects of machine tool structure and position, and was able to predict the errors under different working conditions. The proposed model exhibited good generalization ability.
ADVANCES IN MANUFACTURING
(2023)
Article
Engineering, Manufacturing
Bing Guo, Qingyu Meng, Guicheng Wu, Qingliang Zhao, Shuai Li
Summary: The research focuses on the precision grinding of micro-tooth internal threads using coarse-grains CBN wheels. The study provides optimal parameters and machining conditions for achieving high precision and hardness in internal threads.
JOURNAL OF MANUFACTURING PROCESSES
(2022)
Article
Optics
An Jin, Jie Lin, Bin Liu, Lei Wang, Peng Jin
Summary: The study proposed using moire fringes technology (MFT) to detect the dynamic radial error motion of high-speed spindles (HSS), successfully improving measurement accuracy and meeting the requirements for high speeds.
OPTICS AND LASERS IN ENGINEERING
(2022)
Article
Automation & Control Systems
Wenjie Cao, Haolin Li, Qiang Li
Summary: A new method for calculating the optimal combination of measuring points to improve the machining accuracy of the thermal error prediction model of CNC machine tools was proposed. The method combines correlation analysis, mutual information, principal component analysis, and multilinear regression to establish the thermal error prediction model. Experimental results show that the method demonstrates high accuracy in predicting thermal errors under variable ambient conditions and outperforms alternative modeling methods.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2022)
Article
Materials Science, Multidisciplinary
Yue Ma, Zhiqiang Liang, Kun Wan, Rongbin Cai, Linfeng Yi, Jianfei Li, Fei Wang, Xu Zhao, Rui Chen, Xibin Wang
Summary: In this study, the H-shaped chisel edge micro-drill (HCE-MD) was developed to improve tool life and micro-hole machining quality. The unique characteristic of the HCE-MD is the inner edge formed through chisel edge thinning. The inner edge enables positive rake cutting, reducing the machining area of the workpiece extruded by the cutting edge with a negative rake angle. The HCE-MD was fabricated using a six-axis CNC grinding machine, and the grinding process parameters were optimized based on orthogonal grinding tests and grey relational grade theory. The experiments demonstrated that the HCE-MD outperformed common micro drills in terms of lower thrust force, better micro-hole roundness accuracy, and reduced wear on the chisel edge and flank.
Article
Engineering, Mechanical
Quanbo Lu, Dong Zhu, Meng Wang, Mei Li
Summary: Traditional methods for thermal error prediction in CNC machine tools ignore the correlation between physical and virtual data, resulting in low prediction accuracy. To solve this problem, we propose a thermal error prediction approach based on digital twins and long short-term memory (DT-LSTM), which combines the simulation capabilities of digital twins and data processing capabilities of LSTM. The experimental results show that DT-LSTM outperforms the single method by nearly 11%, improving the prediction performance and robustness of thermal error.
Article
Chemistry, Multidisciplinary
Xin Song, Feifan Ke, Keyi Zhu, Yinghui Ren, Jiaheng Zhou, Wei Li
Summary: This paper proposes the use of mechano-chemical micro-grinding tools to process single-crystal silicon, achieving high-quality and efficient processing of small parts. The theoretical analysis model of grinding force was established and verified, and the temperature field distribution during mechano-chemical micro-grinding was simulated and studied. Special micro-grinding tools were developed and tested, showing improved chemical activity and achieving low-damage processing.
APPLIED SCIENCES-BASEL
(2023)
Article
Optics
Pengcheng Yao, Shaoyan Gai, Feipeng Da
Summary: This paper proposes a novel fringe projection strategy to resist motion error and analyzes the model of motion error. Unlike traditional methods, the proposed method can directly obtain accurate phase, making it more efficient without the need for post-processing procedures.
OPTICS AND LASER TECHNOLOGY
(2023)
Article
Automation & Control Systems
Lei Song, Kuo Liu, Di Zhao, Song Zhang, Zewei Zhang, Yongqing Wang
Summary: A spindle axial time-varying thermal error compensation method based on edge computing was studied to reduce the impact of the error on the accuracy consistency of high-end parts in horizontal boring and milling machine tool (HBMMT). The error model was established based on the speed and acceleration of spindle temperature change, and the compensation value was acquired using edge computing. The error was then compensated by offsetting the coordinate origin, resulting in a reduced error fluctuation range and improved accuracy stability of HBMMT.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2023)
Article
Materials Science, Multidisciplinary
I. Bobkova, A. M. Bobkov, Wolfgang Belzig
Summary: Thermally induced magnetization dynamics is a flourishing research field with potential applications in information technology. The study of a magnetic domain wall interacting with an adjacent superconductor in a thermal gradient has shown that the spin-transfer torques produced in this system are large enough to result in domain wall velocities 10(3) times larger than previously predicted, due to the combined effects of the giant thermoelectric effect and the creation of equal-spin pairs in the superconductor.