Article
Engineering, Manufacturing
Shijie Dai, Xiaojun Wang, Huibo Zhang, Birong Wen
Summary: Selecting appropriate grinding parameters is crucial when grinding wind turbine blades by robot to prevent grinding burn and ensure surface quality. By establishing a heat source model and conducting numerical simulations, it is possible to predict and control the grinding temperature effectively, resulting in high-quality surface grinding.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE
(2021)
Article
Engineering, Manufacturing
Ziling Wang, Lai Zou, Lian Duan, Xifan Liu, Chong Lv, Mingwang Gong, Yun Huang
Summary: A novel passive compliance control method was proposed in this study to stabilize the normal grinding force in robotic grinding of nickel-based superalloy blade. The control accuracy of normal grinding force increased by 64.81% using this method, significantly improving the surface profile accuracy to 0.10309 mm.
JOURNAL OF MANUFACTURING PROCESSES
(2021)
Article
Automation & Control Systems
Ziling Wang, Lai Zou, Yilin Mu, Heng Li, Wenxi Wang, Yun Huang
Summary: This paper proposes a novel region-based force control strategy for achieving high-precision grinding. By considering regional division and calculating ideal grinding force, the traditional robotic belt grinding method is improved. An adaptive impedance controller is also designed to enhance force control accuracy. Experimental results demonstrate the effectiveness and advantages of this approach.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2023)
Article
Automation & Control Systems
Hongyao Zhang, Lun Li, Jibin Zhao, Jingchuan Zhao
Summary: The study develops a hybrid force/position anti-disturbance control strategy based on fuzzy PID control to improve the quality of grinding aviation blades with industry robots. By utilizing gravity compensation technology and dual fuzzy PID control, the control system's disturbance rejection capability is enhanced. Through stability and steady-state error analysis, the validation of the control system's feasibility is proven. Experimental results demonstrate better control effect and grinding quality compared to traditional PID control.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2021)
Article
Chemistry, Multidisciplinary
Haolin Jia, Xiaohui Lu, Deling Cai, Yingjian Xiang, Jiahao Chen, Chengle Bao
Summary: In recent years, high-performance grinding has shifted from traditional manual grinding to robotic grinding. Accurate material removal poses a challenge for workpieces with complex profiles. Digital processing of grinding has shown great potential for optimizing manufacturing processes and operational efficiency, leading to the inevitable trend of quantifying the material removal process. This research establishes a three-dimensional model of the grinding workstation, designs the blade back arc grinding trajectory, and develops a prediction model for blade material removal depth (MRD) using the Adaptive Neuro-Fuzzy Inference System (ANFIS). Experimental investigations using the Taguchi method and Analysis of Variance (ANOVA) revealed the impact of certain elements on the outcomes and demonstrated the superior performance of ANFIS compared to other prediction models.
APPLIED SCIENCES-BASEL
(2023)
Article
Robotics
Lun Li, Zhengjia Wang, Guang Zhu, Jibin Zhao
Summary: This paper proposes a position-based force tracking adaptive impedance control strategy to improve the grinding quality of aeroengine complex curved parts. The method considers the stiffness damping environmental interaction model and modifies the reference trajectory to achieve adaptive grinding. A forgotten Kalman filter is used to denoise the force information, and a three-step gravity compensation process is proposed to obtain accurate contact force between tool and workpiece.
JOURNAL OF FIELD ROBOTICS
(2023)
Article
Engineering, Multidisciplinary
Kun Feng, Yuan Xiao, Zhouzheng Li, Zhinong Jiang, Fengshou Gu
Summary: In this article, we propose a method that utilizes advanced signal processing and machine learning techniques to solve the problems of early warning of blade failure and difficulty in locating the failure. The method accurately calculates the blade passing frequency from gas turbine broadband casing vibration using Sparse Harmonic Product Spectrum (SHPS). It also separates the blade-related vibration from casing vibration in strong noise using Vold-Kalman filter and adaptive parameter optimization process (AVKF). Based on the blade-related vibration, a gas turbine blade condition model is built in an unsupervised learning manner, which can detect potential blade failures earlier and more accurately compared to conventional threshold methods. Furthermore, three coefficients are constructed to identify the blade fault location in a multi-stage system based on the vibration characteristics.
Article
Computer Science, Interdisciplinary Applications
Kangkang Song, Guijian Xiao, Shulin Chen, Xuetao Liu, Yun Huang
Summary: Robotic abrasive belt grinding has been successfully applied to the grinding and polishing of aerospace parts. However, it is very difficult to control the actual removal depth and force of the polished surface due to the flexible characteristics of robotic abrasive belt grinding and the time-varying characteristics of the polishing contact force, as well as the plastic and difficult-to-machine material properties of Inconel 718 alloy, which brings great challenges to robot automatic polishing.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2023)
Article
Engineering, Mechanical
Xiangrui Zeng, Liwen Wang, Xin Lu
Summary: The mechanism of aero-engine turbine blade grinding descaling was explored through simulation and experiment. The parameters of the grinding descaling simulation model were determined by experiment and theoretical analysis. The simulation with single grain was conducted using FEM, and the correctness of the results was verified by experiment. The results showed that the grinding cracks were direct and brightness, and the forces varied with different grinding parameters.
JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY
(2022)
Article
Engineering, Mechanical
Jun Zhang, Wei-dong Liu, Fei-long Liu, De-liang Fan, Chuan Yu, Zhi-biao Xu, Wu-lin Zhang
Summary: This study investigates the surface integrity of the fifth tenon tooth root of second stage high pressure turbine blades, and finds that cracks mainly occur along the near-surface carbides. Grinding burn and stress concentration during contact with the grinding wheel are the main causes of crack initiation and propagation.
ENGINEERING FAILURE ANALYSIS
(2022)
Article
Engineering, Multidisciplinary
FengTao Han, SikYuen Tam, ZhiHong Cao, XingWei Zhao, Bo Tao, Han Ding
Summary: This paper proposes a nonlinear impedance control method for collaborative robotic grinding. The nonlinear force feedback is designed to compensate for the nonlinear stiffness of the environment, ensuring system stability. A target trajectory adaptation strategy is studied to meet force tracking requirements, and a switching law between trajectory tracking and force tracking is proposed for complex grinding tasks. Experimental results demonstrate that the nonlinear impedance control achieves stable grinding force and better grinding quality than linear impedance control.
SCIENCE CHINA-TECHNOLOGICAL SCIENCES
(2023)
Article
Green & Sustainable Science & Technology
Musa Ozkan, Onur Erkan
Summary: This study investigates the influence of distributed passive roughness on the aerodynamic performance of the NACA 63-415 airfoil. The results show that the right sort of roughness can significantly enhance the aerodynamic performance of wind turbine blades under certain flow conditions.
Review
Engineering, Multidisciplinary
Buxin Zhang, Shujing Wu, Dazhong Wang, Shanglei Yang, Feng Jiang, Changhe Li
Summary: With the continuous improvement of thrust-to-weight ratio and endurance in advanced aero-engines, higher requirements are being imposed on blade surface quality. Robot abrasive belt grinding offers excellent flexibility, convenient scheduling, strong adaptability, and low cost advantages. However, factors such as low repeated positioning accuracy, weak structural stiffness, and elastic deformation during belt grinding significantly influence the surface quality and contour accuracy of robot belt grinding.
Article
Automation & Control Systems
Zeyuan Yang, Xiaohu Xu, Minxing Kuang, Dahu Zhu, Sijie Yan, Shuzhi Sam Ge, Han Ding
Summary: This study develops a dynamic compliant force control (DCFC) strategy for the robotic belt grinding system to suppress vibrations and over-grinding phenomenon. By investigating the vibration mechanism and constructing vibration models, the vibrations are decomposed into three components: free, accompanying, and forced vibrations. The DCFC strategy, which considers mechanical compliance and dynamic closed-loop control of the grinder damping, is presented. Results from experiments show that the DCFC strategy significantly reduces vibration amplitude and improves grinding stability and quality.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2023)
Article
Automation & Control Systems
Jun Wu, Jun Cheng, Baoyu Liu, Tao Yu, Chunchun Gao
Summary: This paper compares the processing quality of grain-arranged grinding wheels, with different grain arrangements, to conventional grinding wheels in the grinding of single-crystal silicon. By considering material removal, grain interactions, and arrangement parameters, a grinding force model is built for the grain-arranged wheel. The experiments find that grain arrangement has a significant influence on the machined surface quality. The rational and orderly arrangement improves surface quality and stability, but is not always better than the conventional wheel. The arranged wheel in oblique rectangle arrangement has smaller average force and more stable momentary force than the conventional wheel.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2022)
Article
Computer Science, Interdisciplinary Applications
Shenglin Wang, Jingqiong Zhang, Peng Wang, James Law, Radu Calinescu, Lyudmila Mihaylova
Summary: In Industry 5.0, Digital Twins provide flexibility and efficiency for smart manufacturing. Deep learning techniques are used to enhance the Digital Twin framework, enabling the detection and classification of human operators and robots during the manufacturing process. The framework shows promising results in accurately detecting and classifying actions of human operators and robots in various scenarios.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Yi Liu, Junpeng Qiu, Jincheng Wang, Junhe Lian, Zeran Hou, Junying Min
Summary: In this study, a double-sided robotic roller forming process was developed to form ultrahigh strength steels to thin-walled profiles. Synchronized laser heating and iterative path compensation method were used to reduce forming forces and achieve high-precision forming.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Zequn Zhang, Yuchen Ji, Dunbing Tang, Jie Chen, Changchun Liu
Summary: This paper proposes a digital twin system for human-robot collaboration (HRC) that overcomes the limitations of current methods and improves the overall performance. The system includes a human mesh recovery algorithm and uncertainty estimation to enhance the system's capabilities. Experimental results demonstrate the superiority of the proposed methods over baseline methods. The feasibility and effectiveness of the HRC system are validated through a case study involving component assembly.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Junmin Park, Taehoon Kim, Chengyan Gu, Yun Kang, Joono Cheong
Summary: This paper proposes a highly reliable and accurate collision estimator for robot manipulators in human-robot collaborative environments using the Bayesian approach. By assuming robot collisions as dynamic Markov processes, the estimator can integrate prior beliefs and measurements to produce current beliefs in a recursive form. The method achieves compelling performance in collision estimation with high accuracy and no false alarms.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Meng Wang, Kaixuan Chen, Panfeng Wang, Yimin Song, Tao Sun
Summary: In this study, a novel teleoperation machining mode and control strategy were proposed to improve efficiency and accuracy in small batch production of large casting parts. By using variable motion mapping and elastic compensation, constant cutting force was achieved, and the workpiece was protected by employing forbidden virtual fixtures and movement constraints on the slave robot.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Zhaoyu Li, Dong He, Xiangyu Li, Xiaoke Deng, Pengcheng Hu, Jiancheng Hao, Yue Hou, Hongyu Yu, Kai Tang
Summary: This paper presents a novel algorithm for planning a five-axis inspection path for arbitrary freeform surfaces. By converting the inspection path planning problem into a set-covering problem, the algorithm generates a near-minimum set of inspection paths that satisfy necessary constraints. Both computer simulation and physical inspection experiments confirm the effectiveness and advantages of the proposed method.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Hang Zhang, Wenhu Wang, Shusheng Zhang, Yajun Zhang, Jingtao Zhou, Zhen Wang, Bo Huang, Rui Huang
Summary: This paper introduces a novel framework based on deep reinforcement learning for generating machining process routes for designated parts. The framework utilizes graph representations of parts and employs convolutional graph neural networks for effective processing. Experimental results demonstrate the ability of the proposed method to generate efficient machining process routes and overcome limitations of traditional methods.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Regina Kyung-Jin Lee, Hao Zheng, Yuqian Lu
Summary: Future manufacturing will witness a shift towards collaboration and compassion in human-robot relationships. To enable seamless knowledge transfer, a unified knowledge representation system that can be shared by humans and robots is essential. The Human-Robot Shared Assembly Taxonomy (HR-SAT) proposed in this study allows comprehensive assembly tasks to be represented as a knowledge graph that is understandable by both humans and robots. HR-SAT incorporates rich assembly information and has diverse applications in process planning, quality checking, and human-robot collaboration.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Jianhui He, Lefeng Gu, Guilin Yang, Yiyang Feng, Silu Chen, Zaojun Fang
Summary: This paper presents a new modular kinematic error model for collaborative robots and proposes a portable self-calibration device to improve their positioning accuracy.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Hongwei Sun, Jixiang Yang, Han Ding
Summary: This paper proposes an asymmetrical FIR filter-based tool path smoothing algorithm to fully utilize the joint drive capability of robot manipulators. The algorithm considers the pose-dependent dynamics and constraints of the robot and improves motion efficiency by over 10% compared to traditional methods.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Dongsheng Ge, Huan Zhao, Yiwei Wang, Dianxi Li, Xiangfei Li, Han Ding
Summary: This paper focuses on learning a stable force control policy from human demonstration during contact transients. Based on the analysis of human demonstration data, a novel human-inspired force control strategy called compliant dynamical system (CDS) is proposed. The effectiveness of the proposed method is validated through simulation and real-world experiments.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Xuepeng Huang, Zhenzhong Wang, Lucheng Li, Qi Luo
Summary: This study models the stiffness of a robot and modifies the tool influence function (TIF) with the Preston equation in order to achieve uniform surface quality in robotic bonnet polishing (RBP) of optical components. Experimental results validate the accuracy of the modified model.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Mario D. Fiore, Felix Allmendinger, Ciro Natale
Summary: This paper presents a constraint-based programming framework for task specification and motion optimization. The framework can handle constraints on robot joint and Cartesian coordinates, as well as time dependency. It also compares with existing methods and provides numerical support through illustrative examples and case studies.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Yongxue Chen, Yaoan Lu, Ye Ding
Summary: This paper presents an optimization method for directly generating a six-degree-of-freedom toolpath for robotic flank milling. By optimizing the smoothness of the toolpath and the stiffness of the robot, the efficiency, accuracy, and finish of the machining are improved.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Chungang Zhuang, Haoyu Wang, Han Ding
Summary: This article proposes an end-to-end pipeline for synchronously regressing potential object poses from an unsegmented point cloud. It extracts point pair features and uses a voting architecture for instance feature extraction, along with a 3D heatmap for clustering votes and generating center seeds. An attention voting module is also employed to adaptively fuse point-wise features into instance-wise features. The network demonstrates robustness and improved performance in pose estimation.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)