Article
Acoustics
Yongjian Ji, Liyong Wang, Yue Song, Hongjun Wang, Zhibing Liu
Summary: This study proposed a dynamic stability prediction method for robotic milling based on high-order interpolation polynomials, and used stability lobe diagrams to select cutting parameters and analyze chatter stability under different robot postures and cutter orientations. The research results showed that the dynamic characteristics of the tool during milling are influenced by the cutting direction and tool structure, and increasing the lead or tilt angle can improve the milling stability.
JOURNAL OF SOUND AND VIBRATION
(2022)
Article
Computer Science, Interdisciplinary Applications
Kai Li, Chaochao Qiu, Yongcheng Lin, Mingsong Chen, Xianshi Jia, Bin Li
Summary: A weighted adaptive joint distribution adaptation transfer learning method was proposed in this paper to predict the position-speed dependent tool tip dynamics of different machine tools with different service time. By training a Kriging regression model, the proposed method showed minimum error in predicting the natural frequency and damping ratio compared to the current method.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Multidisciplinary Sciences
Yun Zhu, Miao Xie, He Wang
Summary: This study investigates the influence of multiple interactions between coal and rock and the velocity effect of the cutting head on the flutter stability of the cantilever roadheader. By considering the physical characteristics of coal and rock, as well as the structural and motion parameters of the cutting head, a cutting dynamic model is constructed. An improved discrete method based on Newton-Lagrange mixed interpolation is proposed to clarify the influence of regeneration effect and velocity effect on cutting flutter stability. The results show that the improved fully discrete method can accurately predict the actual cutting state.
SCIENTIFIC REPORTS
(2022)
Article
Engineering, Manufacturing
Oier Franco, Xavier Beudaert, Alex Iglesias, Zoltan Dombovari, Kaan Erkorkmaz, Jokin Munoa
Summary: This paper investigates the structural chatter vibrations in large machine tool applications and emphasizes the importance of accurate dynamic characterization for predicting stability lobes. The study optimizes the tool radial engagement using the sweep milling force excitation method and proposes an alternative spectra computation technique to improve the signal to noise ratio. The receptance measurement is demonstrated using time domain simulations and applied in a large-scale three axis machining centre, resulting in more accurate stability boundary predictions.
INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE
(2022)
Article
Acoustics
Chunlei Song, Zhike Peng, Dingtang Zhao, Xiaoliang Jin
Summary: The paper proposes a whole discretization method for faster and more accurate prediction of milling stability. The method includes discrete vibration velocities in addition to vibration displacements by rebuilding the integrated matrix. This avoids prediction errors caused by separate discretization of the cutting force coefficient matrix and vibration variables. The milling stability is determined using the discrete map of the state based on Floquet theory.
JOURNAL OF SOUND AND VIBRATION
(2023)
Article
Engineering, Electrical & Electronic
Xin Tong, Qiang Liu, Liuquan Wang, Pengpeng Sun
Summary: This paper presents a parameter optimization method to avoid chatter in the five-axis milling process. The dynamic milling system is modeled and the stability is analyzed by introducing the semi-discretization method. Additionally, a multi-frequency solution is presented for predicting the stability of the spindle-cutter system and workpiece system. The verification experiment shows the predictive accuracy of the chatter model and the validity of the proposed optimization method.
Article
Acoustics
Arjun Patel, Devang Kumar Talaviya, Mohit Law, Pankaj Wahi
Summary: This study presents a method to tune an absorber integrated within a rotating milling tool holder while considering its speed-dependent characteristics, aiming to improve chatter-free machining capability. By optimizing the absorber using this approach, a significant improvement in chatter-free machining capability is achieved compared to traditional methods.
JOURNAL OF SOUND AND VIBRATION
(2022)
Article
Engineering, Mechanical
Weitao Li, Liping Wang, Guang Yu, Ding Wang
Summary: A novel thin-walled parts time-varying dynamics updating method based on a degree of freedom reduction model is proposed for milling chatter prediction. The method efficiently updates the dynamics of thin-walled parts and integrates into a milling dynamic model for chatter analysis, providing accurate predictions through a series of milling experiments.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2021)
Article
Automation & Control Systems
Long Wu, Guofeng Wang, Haitao Liu, Tian Huang
Summary: This study proposes an effective method to analyze the stability of the robot milling process by combining robot structural dynamics with cutting forces. The results show that the stability lobes are highly dependent on the pose and primarily dominated by lower-order structural modes.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2022)
Article
Multidisciplinary Sciences
Lijun Lin, Mingge He, Qingyuan Wang, Congying Deng
Summary: In this paper, an efficient method was introduced to predict the milling stability dependent on tool information, and an optimization model was established to maximize the material removal rate. The particle swarm optimization algorithm was used to solve the optimization model and provide the optimal configuration of machining parameters and tool information.
Article
Engineering, Mechanical
Vahid Ostad Ali Akbari, Yaser Mohammadi, Michal Kuffa, Konrad Wegener
Summary: An accurate description of machine tool dynamics is crucial for health monitoring, chatter prevention, and improvement of manufacturing accuracy. However, current methods fail to consider the variations in dynamics during operational conditions. This paper proposes an industrial-friendly method to estimate the in-process structural dynamics of machine tools. The method utilizes forced vibrations during milling operations to determine the cross Frequency Response Function (FRF) of the coupled structure, and an optimization algorithm is employed to tune the modal parameters until the predicted FRFs match the experimentally determined FRFs. The identified in-process dynamics are used for stability prediction and cutting force estimation.
INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES
(2023)
Article
Automation & Control Systems
Chunlei Song
Summary: A novel high-order discretization method is proposed to predict milling stability with increased accuracy and efficiency considering the differential of directional cutting coefficient and vibration velocities. The algorithm reconstructs the cutting force coefficient matrix and calculates the monodromy matrix using the temporal finite element analysis method, improving computational time. The proposed method reduces computational cost by 91-95% with the same level of error tolerance.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2023)
Article
Engineering, Multidisciplinary
Masahiro Makino, Koji Utsumi, Hiroyuki Sasahara
Summary: Turn-milling is an efficient machining method that allows for milling difficult-to-cut materials by milling a rotating work material. It has advantages such as lower cutting temperature, high chip disposability, and the ability to reduce workpiece diameter in one tool path. However, there is limited research on chatter vibration in turn-milling, especially in the context of 5-axis turn-milling. This study aims to investigate the effect of tool posture on chatter vibration and has successfully predicted chatter stability through simulations and confirmed the findings through cutting experiments.
PRECISION ENGINEERING-JOURNAL OF THE INTERNATIONAL SOCIETIES FOR PRECISION ENGINEERING AND NANOTECHNOLOGY
(2023)
Article
Chemistry, Physical
Mikel Casuso, Antonio Rubio-Mateos, Fernando Veiga, Aitzol Lamikiz
Summary: The present study examines the feasibility of thin floor milling without back support, using flexible fixtures, in terms of vibration and roughness. The effects of material removal on modal parameters and chatter appearance were analyzed. The relationship between surface roughness and chatter frequency, tooth passing frequency, and spindle frequency was studied. The ploughing effect during milling was also observed, and the factors leading to its occurrence were analyzed, in order to prevent it.
Article
Engineering, Mechanical
Huihui Miao, Chenyu Wang, Changyou Li, Wenjun Song, Xiulu Zhang, Mengtao Xu
Summary: This research focuses on developing a dynamic model of the whole machine tool considering the milling process to predict vibration response and dynamic characteristics. The proposed model is evaluated by measuring and comparing frequency response functions, cutting forces, and vibration responses under different cutting conditions. The experimentally confirmed model is used for parameter analysis, revealing the influence of preload and cutting conditions on the dynamic characteristics of the machine tool during machining.
INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES
(2023)
Article
Acoustics
Huilin Zhou, Jianfu Zhang, Pingfa Feng, Dingwen Yu, Zhijun Wu
Article
Computer Science, Artificial Intelligence
Wentao Luo, Jianfu Zhang, Pingfa Feng, Dingwen Yu, Zhijun Wu
KNOWLEDGE-BASED SYSTEMS
(2020)
Article
Instruments & Instrumentation
Huilin Zhou, Jianfu Zhang, Pingfa Feng, Dingwen Yu, Jianjian Wang
SMART MATERIALS AND STRUCTURES
(2020)
Article
Acoustics
Huilin Zhou, Jianfu Zhang, Pingfa Feng, Dingwen Yu, Zhijun Wu
Summary: This study proposes a giant magnetostrictive ultrasonic transducer suitable for rotary ultrasonic machining systems, with a mathematical model established for impedance compensation optimization to maximize the use of ultrasonic energy. Experimental results verify the effectiveness of the optimum compensation capacitance and the ability to obtain the resonance zone with the lowest energy consumption.
Article
Engineering, Manufacturing
Shahzad Ahmad, Jianfu Zhang, Pingfa Feng, Dingwen Yu, Zhijun Wu
JOURNAL OF MANUFACTURING PROCESSES
(2020)
Article
Automation & Control Systems
Ke Ma, Jianfu Zhang, Pingfa Feng, Dingwen Yu, Zhijun Wu
Summary: The study established a mathematical model for calculating the resonant frequency of ultrasonic straight-blade tools with variable cross-sectional areas, and utilized the relationship between parameters and force to calculate system frequency changes, with verification experiments showing a high level of matching with actual values.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2021)
Article
Computer Science, Artificial Intelligence
Wentao Luo, Jianfu Zhang, Pingfa Feng, Dingwen Yu, Zhijun Wu
Summary: In the context of intelligent tightening tasks, applying reinforcement learning faces challenges in transforming expert knowledge into a mathematical expression, leading to repeated learning in the face of changing assembly standards. To tackle these issues, a dynamic reinforcement learning approach based on deep transfer learning was proposed, aiming to enhance agent learning efficiency and algorithm adaptability while tackling reward function design difficulties.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Zhao Ganlin, Feng Pingfa, Zhang Jianfu, Yu Dingwen, Wu Zhijun
Summary: This study proposes a method for information integration and instruction authoring for augmented assembly systems, which establishes design guidelines and information models using Unified Modeling Language, and presents a standard rapid development process.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2021)
Article
Engineering, Electrical & Electronic
Bohao Huang, Pingfa Feng, Jianfu Zhang, Dingwen Yu, Zhijun Wu
Summary: This research presents a novel positioning module for UAV monitoring, achieving improved accuracy and frequency through calibration and sensor fusion algorithms. The main contribution lies in the design of the positioning module and validation of the sensor fusion algorithm in low-cost sensor settings, showcasing significant advancements in positioning technology.
IEEE SENSORS JOURNAL
(2021)
Article
Acoustics
Jianfu Zhang, Ke Ma, Jianjian Wang, Pingfa Feng, Shahzad Ahmad
Summary: This study proposes a method that combines multiple parameters to accurately track the resonance frequency of an ultrasonic system, and verifies the feasibility of this method through theoretical analysis and experiments. The results show that this method can improve tracking accuracy and response rate, and effectively reduce cutting-induced defects in ultrasonic cutting.
IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL
(2022)
Article
Computer Science, Artificial Intelligence
Wentao Luo, Pingfa Feng, Jianfu Zhang, Dingwen Yu, Zhijun Wu
Summary: A proposed Improved Deep Convolution Generative Adversarial Transfer Learning Model (IDCGAN-TM) integrates generative learning, feature learning, and transfer learning modules to effectively address the limited data problem in assembly equipment and achieve excellent performance in assembly quality diagnosis.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2022)
Article
Engineering, Manufacturing
Hailong Yang, Jianjian Wang, Jianfu Zhang, Pingfa Feng, Zhijun Wu, Dingwen Yu
Summary: This article investigates the processing characteristics and material removal mechanism of silica aerogel composites. Experimental results show that burrs and pits decrease with ultrasonic amplitude, increase with tool diameter, and up-milling provides better processing quality than down-milling. The main removal mechanisms are identified as shearing and pulling off.
JOURNAL OF MANUFACTURING PROCESSES
(2021)
Article
Computer Science, Artificial Intelligence
Wentao Luo, Jianfu Zhang, Pingfa Feng, Haochen Liu, Dingwen Yu, Zhijun Wu
Summary: The paper proposes a MAPPO method that improves the efficiency and accuracy of traditional PPO methods through probabilistic trees and adaptive reward mechanisms, allowing the assembly system to autonomously correct errors. The verification on the Unity simulation engine demonstrates the superiority of the MAPPO method.
APPLIED INTELLIGENCE
(2021)
Proceedings Paper
Automation & Control Systems
Luo Wentao, Feng Pingfa, Zhang Jianfu, Yu Dingwen, Wu Zhijun, Liu Haochen
2020 4TH INTERNATIONAL CONFERENCE ON CONTROL ENGINEERING AND ARTIFICIAL INTELLIGENCE (CCEAI 2020)
(2020)
Article
Computer Science, Information Systems
Ruoyu Cui, Jianfu Zhang, Pingfa Feng, Dingwen Yu, Zhijun Wu
