Most Read

Published in last 1 year |

In last 2 years |

In last 3 years |

All

Please wait a minute...


For Selected: Download Citations EndNote Ris BibTeX Toggle Thumbnails

Select

Research on Product Function Expansion Driven by Text Mining and Patent Data Collaboration LIN Wenguang, LIU Xiaodong, XIAO Renbin Journal of Mechanical Engineering    2024, 60 (13): 56-70.   DOI: 10.3901/JME.2024.13.056 Abstract （2469）      PDF（pc） （940KB）（1701）       Knowledge map    Save Function expansion is an important way to achieve innovative product design, and data-drivenis also the key supporting technology for product function expansion. In this context, a product function expansion method driven by text mining and patent data collaboration is proposed and expected to provide a quantitative research method for changing and upgrading existing products. Firstly, the function-structure mapping information of the target product are analyzed, then a partial hypergraph model based on existing network models is proposed to calculate the weight of product's components. Secondly, four extracting product functional and structural knowledge, text data of us patent is retrieved and obtained, then part of speech tagging (POS tagging) and dependency parsing (DP) are used to construct mining rules to extract subject-action-object (SAO) in sentences. Thirdly, patent text is used as the corpus and BERT(Bidirectional encoder representations from transformers) model is utilized to train word vectors as a tool for finding similar structures and functions, then four function expansion strategies combined with collaborative recommendationalgorithms are proposed as follows: other function expansion, similarity function expansion, similar component’s functions expansion, and similar components’ functions expansion based on the target product components; finally, according to the requirements of enterprise, the case of showerhead is applied to verifies thefeasibility and effectiveness of the method. Reference | Related Articles | Metrics | Comments（0）

Select

Deep Reinforcement Learning-based Integrated Control of Hybrid Electric Vehicles Driven by High Definition Map in Cloud Control System TANG Xiaolin, CHEN Jiaxin, GAO Bolin, YANG Kai, HU Xiaosong, LI Keqiang Journal of Mechanical Engineering    2022, 58 (24): 163-177.   DOI: 10.3901/JME.2022.24.163 Abstract （2086）      PDF（pc） （1390KB）（1018）       Knowledge map    Save In the context of the development of intelligence, connectivity, and new energy, the automotive industry combines computer, information communication, artificial intelligence(AI) to achieve integrated development. Based on the new generation of information and communication technology——cloud control system(CCS) of intelligent and connected vehicles(ICVs), the cloud-level automatic driving of new energy vehicles is realized driven by connected data, which provides innovative planning and control ideas for vehicle driving and power systems. Firstly, based on the resource platform of CCS, the latitude, longitude, altitude, and weather of the target road are obtained, and a high definition(HD) path model including slope, curvature, and steering angle is established. Secondly, a deep reinforcement learning(DRL)-based integrated control method for hybrid electric vehicle(HEV) drive by the HD model is proposed. By adopting two DRL algorithms, the speed and steering of the vehicle and the engine and transmission in the powertrain are controlled, and the synchronous learning of four control strategies is realized. Finally, processor-in-the-loop(PIL) tests are performed by using the high-performance edge computing device NVIDIA Jetson AGX Xavier. The results show that under a variable space including 14 states and 4 actions, the DRL -based integrated control strategy realizes the precise control of the speed and steering of the vehicle layer under the high-speed driving cycle of 172 km, and achieves a fuel consumption of 5.53L/100km. Meanwhile, it only consumes 104.14s in the PIL test, which verifies the optimization and real-time performance of the learning-based multi-objective integrated control strategy. Reference | Related Articles | Metrics | Comments（0）

Select

Review of Technology, Application Status and Development Trend in Multi-arm Cooperative Robots WU Qilin, ZHAO Han, CHEN Xiaofei, ZHAO Yating Journal of Mechanical Engineering    2023, 59 (15): 1-16.   DOI: 10.3901/JME.2023.15.001 Abstract （1569）      PDF（pc） （1421KB）（1583）       Knowledge map    Save As labour shortages and labour costs continue to rise, more and more robots are needed in growing numbers. In many application scenarios, the tasks are complex and varied, the application environment and the conditions are so varied that single-arm collaborative robots are no longer meet the requirements and multi-arm collaborative robotic systems have emerged as an important area for future development. Because of the short time frame for development, a great deal of work is still needed by developers. This research summarizes the current state of technology and applications of multi-arm collaborative robots in a more systematic way and reviews several influential aspects of multi-arm collaborative robots such as applications, mechanism and lightweight, dynamics and control, cooperative technology, and artificial intelligence. On this basis, six directions for future research and development of multi-armed collaborative robots are proposed, based on new developments in artificial intelligence and control, such as the development of application scenarios towards deep human-robot collaboration, more emphasis on high speed, high precision and high work-to-weight ratio in structures and components, and more emphasis on smooth design in dynamics. The collaborative robot system will also develop in a hierarchical and diversified manner, with control methods tending towards adaptive and flexible control and autonomous decision-making, and interaction tending towards multi-dimensional safety protection and natural interaction with multi-information fusion. Reference | Related Articles | Metrics | Comments（0）

Select

High Performance Manufacturing GUO Dongming Journal of Mechanical Engineering    2022, 58 (21): 225-242.   DOI: 10.3901/JME.2022.21.225 Abstract （1542）      PDF（pc） （2509KB）（1778）       Knowledge map    Save With the increasing expansion of application areas and improvement of in-service performance, there is an urgent need for high-end equipment in the fields such as aerospace and aeronautics, energy and power, information and electronics. It is extremely difficult to manufacture these high-end equipment, not only due to their multiple and higher requirements such as loading, transmission, conduction, energy conversion and stealth, but also due to their complex structures, difficult-to-cut materials, and high requirements in surface integrity and/or precision. High performance manufacturing (HPM) is an inevitable choice to address the above mentioned challenges and break the bottleneck of high-end equipment manufacturing. Starting with the characteristics of parts/components/devices, manufacturing requirements and the state-of-the-art manufacturing technologies, this paper clarifies the connotation of HPM, the key issues to be addressed, and the quantitative correlation between design and manufacturing. Subsequently, the general framework and the generalized model of HPM is proposed, and the fundamental elements and criteria are laid out and discussed. Finally, the realization solutions and the key technologies are highlighted with two case studies. It is pointed out that HPM is not only a kind of precision manufacturing and computational manufacturing with the correlation modeling of multi-parameter in design, manufacturing, and service as the core, but also performance-geometry-integrated manufacturing aiming at the precise guarantee of ultimate performance. Reference | Related Articles | Metrics | Comments（0）

Select

Research Status and Development Trend of Wall Climbing Robot MA Jiliang, PENG Jun, GUO Yanjie, CHEN Xuefeng Journal of Mechanical Engineering    2023, 59 (5): 11-28.   DOI: 10.3901/JME.2023.05.011 Abstract （1385）      PDF（pc） （840KB）（1612）       Knowledge map    Save Wall climbing robot is an electromechanical system that can move on the surface of objects and complete operations with multiple degrees of freedom. It is especially suitable for performing special tasks, so it has a good application prospect and broad market demand. According to different adhesion mechanisms, wall climbing robots can be divided into negative pressure adsorption, electrostatic adhesion, gecko-like dry adhesion, bionic wet adhesion and so on. The research status of wall climbing robots at home and abroad is summarized from three aspects: adhesion mechanism, application scope and adhesion characteristics. In order to analyze and compare the load performance of different types of wall climbing robots, an analysis method of robot overall adhesion performance based on specific adhesion energy density is proposed, and a new material and structure design idea is proposed to solve the contradiction between large load and small volume. The application prospect of micro wall climbing robot in aero-engine fault detection is analyzed, and its development trends in the fields of intelligent materials, new driving, miniaturization and collaboration of adhesion mechanism are summarized. Reference | Related Articles | Metrics | Comments（0）

Select

Overview of Key Technologies for Measurement Robots in Intelligent Manufacturing WANG Yaonan, XIE He, DENG Jingdan, MAO Jianxu, LI Wenlong, ZHANG Hui Journal of Mechanical Engineering    2024, 60 (16): 1-18.   DOI: 10.3901/JME.2024.16.001 Abstract （1360）      PDF（pc） （852KB）（1186）       Knowledge map    Save Complex curved components are the core elements of high-end equipment in fields such as aerospace and marine vessels, and their measurement accuracy plays an irreplaceable role in ensuring the quality of high-end equipment manufacturing. To overcome the limitations of traditional manual and specialized manufacturing methods, vision-guided robotic systems provide a new approach for the high-end and intelligent processing of complex curved components, gradually becoming a research hot spot in the field of robotic intelligent manufacturing. Focusing on the 3D measurement methods of robots, this review first summarizes the characteristics of measurement schemes in different manufacturing scenarios according to sensor types and application scenarios, so as to help researchers quickly and comprehensively understand this field. Then, according to the measurement process, key core technologies are categorized as system calibration, measurement planning, point cloud fusion, feature recognition, etc. The major research achievements in various categories over the past decade are reviewed, and the existing research limitations are analyzed. Finally, the technical challenges faced by robotic measurement are summarized, and future development trends are discussed from the perspectives of application scenarios, measurement requirements, measurement methods, etc. Reference | Related Articles | Metrics | Comments（0）

Select

Review on Techniques for Power Battery State of Health Estimation Driven by Big Data Methods WANG Zhenpo, WANG Qiushi, LIU Peng, ZHANG Zhaosheng Journal of Mechanical Engineering    2023, 59 (2): 151-168.   DOI: 10.3901/JME.2023.02.151 Abstract （1303）      PDF（pc） （920KB）（1571）       Knowledge map    Save State of health estimation of power batteries is one of the key algorithms of the battery management systems, which is of great significance for improving power battery energy utilization efficiency, reducing thermal runaway risk, as well as power battery maintenance and residual value evaluation. Comparative analysis has been done on experimental-based, model-based and data-driven methods, and data-driven methods are elaborated from three aspects:dataset construction, health indicators extraction, model establishment. The big data collection methods and data preprocessing methods are summarized. The health indicators extraction methods are compared by their pros and cons and applicable scenarios. The basic principles of different health state estimation models are discussed. The conclusion that model fusion is the direction of future technology development is proposed. Finally, facing the future application scenarios of big data in electric vehicles, the current issue and prospective are depicted. Reference | Related Articles | Metrics | Comments（0）

Select

Research on Large Model for General Prognostics and Health Management of Machinery LEI Yaguo, LI Xiwei, LI Xiang, LI Naipeng, YANG Bin Journal of Mechanical Engineering    2025, 61 (6): 1-13.   DOI: 10.3901/JME.2025.06.001 Abstract （1269）      PDF（pc） （920KB）（1529）       Knowledge map    Save In recent years, various deep learning-based health management models for mechanical equipment have made significant progress. However, existing models tend to be smaller in scale and are typically designed to handle data from specific frequencies, speeds, or modes, focusing on particular components such as gears and bearings to perform tasks like monitoring, diagnosis, and prediction. These models struggle to adapt to new scenarios and lack the capability for continuous evolution. With the increasing precision and complexity of high-end equipment, there is a growing demand for highly general, scalable, and evolvable "one-stop" health management services. Inspired by the trend of generalization in large language models like ChatGPT, which excel in handling diverse data, tasks, and scenarios, a large model for general prognostics and health management of machinery is proposed. First, multimodal data is resampled in the angular domain and segmented to token sequence. Then, the data is input into a Transformer-based information integration foundational model to extract health and degradation information into specific tokens. Finally, these specific tokens are used to perform downstream tasks such as monitoring, diagnosis, and prediction. The proposed large model's baseline performance, multitask synergy, and scalability were verified using fault and long-term degradation datasets. The results show that the proposed large model can simultaneously perform condition monitoring, fault diagnosis, and remaining useful life prediction for multiple objects like bearings and gears. Additionally, the diagnostic and predictive multitasks can effectively collaborate, mutually enhancing performance, and achieving better results compared to single-task models. In few-shot learning and continual learning scenarios, the large model can be rapidly deployed and continuously evolved. Therefore, the proposed large model features high generality, scalability, and sustainability, and is expected to provide universal "one-stop" health management services for mechanical equipment. Reference | Related Articles | Metrics | Comments（0）

Select

Research Progress and Industrialization Development Trend of Chinese Service Robot TAO Yong, LIU Haitao, WANG Tianmiao, HAN Dongming, ZHAO Gang Journal of Mechanical Engineering    2022, 58 (18): 56-74.   DOI: 10.3901/JME.2022.18.056 Abstract （1210）      PDF（pc） （2236KB）（1457）       Knowledge map    Save With the rapid development of service robots, the robots are used in various fields involving economic and social development, such as medical rehabilitation, education and entertainment, domestic services, emergency and disaster relief, public services and commercial applications. Countries around the world attach great importance to the development of service robots and give them key support as a strategic emerging industry, and service robots are great strategic importance. Firstly, the industrial chain of service robots and relevant international organizations are introduced. The development strategies and plans of service robots proposed by developed countries such as the United States, the European Union, Japan and South Korea are expounded. The driving forces and characteristics of the rapid development of service robots are proposed. The leading service robot research institutions and related companies at home and abroad are presented. The development scale of foreign and domestic service robot industry are proposed. Then, based on the introduction of the development status of service robots at home and abroad, it focuses on the status and progress of medical and health robots, home service robots, public service robots, high-end bionic robots, automated warehousing and logistics robots and special robots. The core technologies such as environment perception and motion control of robots, core components, human-computer interaction, and operating systems are proposed. The cross-integration development of service robots and cutting-edge technologies such as AI, big data, and cloud computing are introduced. Finally, some suggestions of the service robot industry development are proposed. Based on the introduction of the progress and cutting-edge trends of service robot technology, it can provide relevant references and suggestions for the development of service robot technology and industrial development. Reference | Related Articles | Metrics | Comments（0）

Select

Federated Transfer Learning Method for Privacy-preserving Collaborative Intelligent Machinery Fault Diagnostics LI Xiang, FU Chunlin, LEI Yaguo, LI Naipeng, YANG Bin Journal of Mechanical Engineering    2023, 59 (6): 1-9.   DOI: 10.3901/JME.2023.06.001 Abstract （1127）      PDF（pc） （16132KB）（1178）       Knowledge map    Save Big data-driven intelligent machinery fault diagnosis methods have achieved great success in the recent years. The high diagnosis accuracies mostly rely on large amounts of labeled condition monitoring data and centralized model training. However, in the real industries, it is usually difficult for a single user to collect sufficient labeled data, that makes the intelligent diagnosis methods less applicable in practice. It is noted that different industrial users may have similar machines and condition monitoring data. Therefore, collaborative model development is promising to address the data scarcity problem. However, data privacy is very important and different users are generally not comfortable sharing private data with others, that results in a challenging collaborative diagnosis problem. A privacy-preserving collaborative intelligent machine fault diagnosis method FedTL is proposed. The private data are used for training without leaving local storage. The high-level representations of shared data are communicated among different users. A soft label-based information transmission method is proposed. Through capturing the relationship between different fault modes of shared data, the diagnosis knowledge of private data can be well delivered. The federated transfer learning framework is formulated, considering different working conditions of different users. The experiments in bearing condition monitoring cases validate the proposed method. The results show the proposed method is a promising tool for privacy-preserving collaborative machine fault diagnosis. Reference | Related Articles | Metrics | Comments（0）

Select

Review of Variable Stiffness Mechanisms in Minimally Invasive Surgical Manipulators SHANG Zufeng, MA Jiayao, WANG Shuxin Journal of Mechanical Engineering    2022, 58 (21): 1-15.   DOI: 10.3901/JME.2022.21.001 Abstract （1081）      PDF（pc） （1547KB）（1129）       Knowledge map    Save Taking one or several small cuts on skin or a body orifice as the path, minimally invasive surgery can significantly reduce the tissue damage, thus representing the future trend of the surgery. To reach a lesion far away from the path, slender and flexible device should be adopted for its adaptability to the complicated body-cavity condition. A surgical manipulator with variable stiffness can fulfill stiffening-softening function of the flexible device, and it thus becomes the key to ensure a safe human-machine interaction, a good precision, and an enough force output of manipulation during the surgery. Focused on the field of minimally invasive surgical manipulator, the current variable stiffness mechanisms are reviewed and classified as those based on jamming, thermally responsive material, shape-locking, antagonistic actuation force, reconfigurable cantilever, and combinations of them. Under the consideration of the application requirements, performances of manipulators in stiffening capability, response time, and space consumption, are firstly compared and discussed under different variable stiffness mechanisms. Next, potential variable stiffness mechanisms that could be applied in manipulators are reviewed, and the prospects and challenges are also analyzed. Finally, the field is summarized and forecasted. It is pointed out that developing new variable-stiffness material and carrying out integrated design of structures and functions based on biomimetic concepts are the main future directions. Reference | Related Articles | Metrics | Comments（0）

Select

Development and Challenge of Forming Manufacturing Technologies for Aerospace Large-Scale Thin-Wall Axisymmetric Curved-Surface Component ZHANG Hongrui, ZHAN Mei, ZHENG Zebang, LI Rui Journal of Mechanical Engineering    2022, 58 (20): 166-185.   DOI: 10.3901/JME.2022.20.166 Abstract （1068）      PDF（pc） （1145KB）（1189）       Knowledge map    Save Thin-walled curved-surface components are a kind of components that are widely used for high-end carrier equipment in the aerospace industry. With the development toward large-sized, light-weight, high-performance, long-life and high-reliability of new generation aerospace vehicles, strategic missiles, and ships, it is urgent to develop manufacturing technologies for large-sized thin-walled curved-surface components. This kind of components is difficult to manufacture because of their thin thickness, large size, curvature changes, extreme size combination, light-weight and high-strength materials, and high-performance requirements. In this paper, the manufacturing technologies of aerospace large-sized thin-walled axisymmetric curved-surface components are reviewed with respect to their development history and classification. Based on the classification, the corresponding applications and latest research progress of these manufacturing technologies are reviewed. Furthermore, the process characteristics, component performances, and the development potentials of these manufacturing technologies are compared. Finally, the development trend and technical challenges of the manufacturing technology of aerospace large-sized thin-walled axisymmetric curved-surface components are summarized. Reference | Related Articles | Metrics | Comments（0）

Select

Simulation Data-driven Enhanced Unsupervised Domain Adaptation for Bearing Fault Diagnosis SHAO Haidong, XIAO Yiming, YAN Shen Journal of Mechanical Engineering    2023, 59 (3): 76-85.   DOI: 10.3901/JME.2023.03.076 Abstract （1003）      PDF（pc） （946KB）（1408）       Knowledge map    Save The existing unsupervised cross-domain fault diagnosis studies of bearing usually utilize sufficient experimental data collected from test rigs as the source domains, the marginal distribution and conditional distribution alignments between domains are difficult to be considered simultaneously, and all source-domain samples are endowed with the same importance in the process of domain adaptation. Aiming at the above challenges, a new method of simulation data-driven enhanced unsupervised domain adaptation for bearing fault diagnosis is proposed. The bearing fault data with rich fault information and sufficient label data obtained by numerical simulation is used to construct the source domain, thus reducing the dependence on the resources of test rigs. An enhanced loss function embedded with the joint max mean discrepancy is designed to achieve simultaneous alignments of marginal and conditional distributions between different domains in unsupervised scenarios. A weight allocation mechanism for source domain samples is developed to measure the similarity between each individual source domain sample and target domain samples through domain prediction error and to adaptively allocate their weights to suppress negative transfer. Two sets of experimental data collected from test rigs are used as the target domains to validate the effectiveness of the proposed method. The results show that the proposed method can fully adapt the deep feature distributions of simulation domain and experimental domain to improve cross-domain fault diagnosis accuracy in unsupervised scenarios. Reference | Related Articles | Metrics | Comments（0）

Select

Journal of Mechanical Engineering    2023, 59 (18): 1-2.   DOI: 10.3901/JME.2023.18.001 Abstract （966）      PDF（pc） （132KB）（854）       Knowledge map    Save Related Articles | Metrics | Comments（0）

Select

Research Progress of Sensory Feedback for Intelligent Upper-limb Prosthesis HU Yawen, JIANG Li, YANG Bin Journal of Mechanical Engineering    2023, 59 (5): 1-10.   DOI: 10.3901/JME.2023.05.001 Abstract （929）      PDF（pc） （677KB）（927）       Knowledge map    Save In recent years, the bidirectional bio-machine interface with the ability of neural control and sensory feedback has become the development trends of intelligent upper limb prosthesis. Most of the research focuses on the mechanism, sensor design and neural control of upper limb prosthesis, while less research on sensory feedback. The lack of reliable sensory feedback reduces the operational performance and limits the practical application of prosthetics. Firstly, the development status of bidirectional bio-machine interface of intelligent prosthesis is briefly summarized. Sensory feedback methods based on transcutaneous electrical nerve stimulation, vibration stimulation and pressure stimulation are introduced in detail. Sensory feedback strategies including sensory substitution, modality matched feedback and somatotopic matched feedback are also discussed. Based on the analysis, the naturalness of upper limb prosthetic sensory feedback and the multimodality of interactive information are prospected. Reference | Related Articles | Metrics | Comments（0）

Select

Challenges and Opportunities of XAI in Industrial Intelligent Diagnosis: Priori-empowered YAN Ruqiang, SHANG Zuogang, WANG Zhiying, XU Wengang, ZHAO Zhibin, WANG Shibin, CHEN Xuefeng Journal of Mechanical Engineering    2024, 60 (12): 1-20.   DOI: 10.3901/JME.2024.12.001 Abstract （899）      PDF（pc） （685KB）（629）       Knowledge map    Save In the era of “big data”, artificial intelligence(AI) has emerged as an important approach in the field of industrial intelligent diagnosis, owing to its powerful data mining and learning capability. It plays a significant role in tasks such as anomaly detection, fault diagnosis, and remaining useful life prediction of mechanical equipment. As mechanical equipment continues to evolve towards larger scale, higher speed, integration and automation, the reliability of diagnostic methods has become crucial. Consequently, the lack of interpretability has become a major obstacle to the practical application of AI technology in the field of diagnosis. To promote the development of AI technology in industrial intelligent diagnosis, a comprehensive review of explainable AI(XAI) methods is provided. Firstly, the concept and principles of XAI are introduced, along with a summary of the main perspective and classifications of current XAI techniques. Subsequently, the research status of inherently explainable AI techniques empowered by signal processing priors and physical knowledge prior from industrial diagnosis is summarized. Finally, the challenges and opportunities associated with priori-empowered XAI are highlighted. Reference | Related Articles | Metrics | Comments（0）

Select

Life Cycle Assessment of Lithium-ion Batteries for Carbon-peaking and Carbon-neutrality: Framework, Methods, and Progress LAI Xin, CHEN Quan-wei, GU Huang-hui, HAN Xue-bing, ZHENG Yue-jiu Journal of Mechanical Engineering    2022, 58 (22): 3-18.   DOI: 10.3901/JME.2022.22.003 Abstract （880）      PDF（pc） （52919KB）（1096）       Knowledge map    Save Driven by the Carbon-peaking and Carbon-neutrality strategic goals, lithium-ion batteries usher in significant development opportunities. Meanwhile, it has become a research hotspot for tracking the life cycle carbon footprint and environmental indicators assessment and faced severe challenges in carbon emission calculation and reduction measures. First, the basic framework, methods,evaluation indicators, and other common problems of the life cycle assessment are briefly summarized. Then, a whole life cycle closed-loop assessment route from "cradle" to "cradle" is proposed for the sustainable development of lithium-ion batteries. The research progress of carbon emission calculation at all stages of the battery life cycle(including battery production, battery use,echelon utilization, battery recycling, and remanufacture) is summarized in detail, the potential research hotspots and difficulties are generalized, and a comprehensive evaluation framework of "Technology-Ecology-Value" is proposed. The opportunities and challenges in lithium-ion batteries' life cycle value assessment are discussed, and the resource and supply chain risks are analyzed.Finally, six potential carbon reduction measures for the whole life cycle of lithium-ion batteries are summarized and prospected, such as energy decarbonization, system innovation, intelligent manufacturing, optimization management, material recovery, and carbon capture. Reference | Related Articles | Metrics | Comments（0）

Select

Review on Fast Numerical Simulation Method for Plastic Forming ZHAN Mei, DONG Yunda, ZHAI Zhuolei, FAN Xiaoguang, SHI Zhipeng, AN Qiang Journal of Mechanical Engineering    2022, 58 (16): 2-20.   DOI: 10.3901/JME.2022.16.002 Abstract （879）      PDF（pc） （743KB）（1076）       Knowledge map    Save Accurate and efficient numerical prediction model is the kernel about the digitization and intellectualization of plastic forming. To study advanced plastic forming of large-scale complex components in real time, there exists three fast simulation method: massive model simplifying or dimensionality reducing, solver algorithm modifying and high-performance parallel computing. And these methods are introduced in terms of reducing model scale, accelerating or avoiding time-consuming steps and improving device efficiency. The two major approaches about model scale reducing are introduced: mesh density dynamic controlling technique and shell element model. Subsequently, a review of some innovative numerical algorithms for improving calculation process is provided, such as machine learning, material point method and virtual element method. Then, the research progress of parallel techniques on homogeneous and heterogeneous computing platforms is discussed. Finally, the application prospect and development of these numerical simulation methods for plastic forming are also presented. Reference | Related Articles | Metrics | Comments（0）

Select

Digital Engineering and Its Ten Application Outlooks TAO Fei, ZHANG Chenyuan, LIU Weiran, ZHANG He, MA Xin, GAO Pengfei, ZHANG Jiankang Journal of Mechanical Engineering    2023, 59 (13): 193-215.   DOI: 10.3901/JME.2023.13.193 Abstract （874）      PDF（pc） （2114KB）（1123）       Knowledge map    Save Relying on physical methods for planning, research, design, manufacturing, test and use of products or systems is usually constrained by time, space, cost and safety, leading to problems such as long development cycle, high operating costs, delayed response, low intelligence, and difficult system optimization. In order to address the above problems, the theory of digital engineering is introduced, which strives to fully utilize both the 'digital power' and 'intelligence power' to enhance the 'capability'. In this paper, firstly a five-phase maturity model of digital engineering is proposed to better understand, further develop and fully utilize of digital engineering based on the analysis of the current digitalization and intelligentization practices and its future development trends. Then, the 'digital power', 'intelligence power' and 'capability' of digital engineering are defined, and the demands and challenges of digital engineering in the era of New IT are expounded in detail. Furthermore, the architecture of digital engineering is designed, which consists of one 'intelligence center' and four threads (physical thread, model thread, data thread and service thread), and eight key supporting technologies are also put forward. Finally, the application outlooks of digital engineering in ten fields are discussed, including digital nuclear power plant, digital aero-engine, digital satellite internet, digital ocean and marine equipment, digital wind tunnel, digital battlefield, digital city, digital computer numerical control machine, digital energy and digital vehicles, expecting to provide references for the scientific organization, intelligent control and system optimization of complex products and systems throughout lifecycle, as well as the construction of digital earth and the development of digital economy. Reference | Related Articles | Metrics | Comments（0）

Select

Digital Twin-driven Smart Human-machine Collaboration: Theory, Enabling Technologies and Applications YANG Geng, ZHOU Huiying, WANG Baicun Journal of Mechanical Engineering    2022, 58 (18): 279-291.   DOI: 10.3901/JME.2022.18.279 Abstract （858）      PDF（pc） （859KB）（2622）       Knowledge map    Save With the evolution of human-cyber-physical systems (HCPS), the relationships between human and machine evolved through different phases: from human-machine coexistence and human-machine interaction to human-machine cooperation and human-machine collaboration. Meanwhile, emerging technologies (e.g., digital twin) empower the industry and society with increased features of automation and intelligence, enhance the capabilities of perception, analyzing, control, and decision making. Those developments provide human-machine collaboration the foundation for paradigm shifting toward human-centric smart manufacturing. In this work, the concept of digital twin-driven smart human-machine collaboration is proposed based on the HCPS theory. By analyzing the evolutions of human-machine relationship and related definitions on human-machine collaboration, the connotation of smart human-machine collaboration is elaborated. The framework of digital twin-driven smart human-machine collaboration is proposed to address the current challenges in human-machine collaboration, from perspectives of physical entities, digital models, connection and interaction, and smart decision for collaborative service. The enabling technologies for smart human-machine collaboration are discussed from the aspects of sensing and integration, computation and analysis, control and execution, e.g., wearable technology, flexible sensing, artificial intelligence, exoskeleton. Furthermore, typical applications of smart human-machine collaboration are presented, including production, architecture construction, healthcare, and ergonomics. It is expected this work can provide a reference for facilitating paradigm shift of human-machine collaboration and the sustainable development of human-machine collaboration. Reference | Related Articles | Metrics | Comments（0）

Select

Research Progress on Positioning Error Compensation Technology of Industrial Robot LIU Wei, LIU Shun, DENG Zhaohui, GE Jimin Journal of Mechanical Engineering    2023, 59 (17): 1-16.   DOI: 10.3901/JME.2023.17.001 Abstract （852）      PDF（pc） （803KB）（827）       Knowledge map    Save Industrial robots play an important role in promoting the development of industrial automation, flexibility and intelligence. The positioning error of robot is the key factor that hinders its application in the manufacturing field. The positioning accuracy of robot determines the quality and accuracy of the products. Error compensation technology is of great significance to improve the positioning accuracy of robots. Based on the clue of positioning error measurement-prediction-compensation, the research progress of open-loop measurement and closed-loop measurement technology, model-based error prediction and non-model-based error prediction methods, online compensation and offline compensation technology is summarized in detail. Finally, the development trends are prospected in order to provide reference for the research of positioning error compensation of industrial robot. Reference | Related Articles | Metrics | Comments（0）

Select

Co-optimization for 3D Printing Porous Structures and Paths under Manufacturing Constraint XIA Lingwei, XIE Yimin, MA Guowei Journal of Mechanical Engineering    2024, 60 (19): 241-249.   DOI: 10.3901/JME.2024.19.241 Abstract （838）      PDF（pc） （587KB）（460）       Knowledge map    Save Porous structures are widely used in engineering due to their superior comprehensive properties.Compared with traditional equal-material and subtractive manufacturing, 3D printing, as a process of additive manufacturing technology, exhibits significant advantages in manufacturing flexibility and efficiency for porous structures.However, the complicated topological form results in discontinuity and uneven filling of printing paths, thus decreasing the fabrication quality and mechanical performance.A co-optimization of structure and path based on Voronoi skeletons is developed to improve this situation.To generate porous structures suitable for 3D printing, path optimization is synergistically considered by applying a manufacturing constraint in the structural design.Periodic or graded Voronoi cells are constructed according to the mechanical condition, aiming to optimize the material layout.Discontinuous paths, which are generated via offsetting Voronoi skeletons, are connected to fulfill global continuity by introducing a depth-first search method.The calculation result indicates that the porous structures generated by the proposed co-optimization method are evenly fabricated by a path without any intersection and solved the issue of the integral multiple of path width.Additionally, printing defects caused by path breakpoints and null nozzle travel are eliminated.The feasibility of the proposed method is validated by the material extrusion additive manufacturing technology.The mechanical test demonstrates that the mechanical performance of porous structures optimized by the proposed method are higher than that of models fabricated by the conventional method due to better printing quality of the former.This research plays a significant role in fulfilling high performance, thus promoting the integrated design and fabrication of material-structure-performance for 3D printing porous structures. Reference | Related Articles | Metrics | Comments（0）

Select

High-performance Optical Manufacturing DAI Yifan, PENG Xiaoqiang, XUE Shuai, JIANG Zhuangde Journal of Mechanical Engineering    2023, 59 (21): 1-14.   DOI: 10.3901/JME.2023.21.001 Abstract （835）      PDF（pc） （600KB）（676）       Knowledge map    Save High-end equipment such as fusion ignition, synchrotron radiation, lithography machine, space exploration, reconnaissance and warning require to achieve a series of unprecedented extreme, various and complex performance. The key optical components, such as high energy/power laser elements, synchrotron radiation mirrors, mask plates and photolithographic objective, space exploration X-ray mirrors, are fatal to these systems to achieve the extreme performance of focusing, extremely high energy output, extremely high peak power, extreme size of beam focusing and pattern transfer with nano scale accuracy. In order to realize the extreme performance of these high-end equipment, the optical manufacturing of the key components is required to be high accuracy, low damage, low stress, clean manufacturing and integration of function and structure, and it is required to achieve high performance under the constraints of multiple physical parameters. The traditional optical manufacturing methods aiming at improving the accuracy are faced with challenges. It is urgent for optical manufacturing methods to realize the transformation from manufacturing accuracy to manufacturing performance. The study preliminarily summarizes the recent work of high performance optical manufacturing of optical components and ultra-precision parts. The characteristics of typical components made by high performance optical manufacturing techniques, optical manufacturing requirements and optical manufacturing technologies have been summarized. The connotation, key technologies and development trend of high performance optical manufacturing have been tried to be clarified. At the end of the paper, application examples of high performance optical manufacturing have been given. Reference | Related Articles | Metrics | Comments（0）

Select

Digital-twin Collaborative Technology for Human-robot-environment Integration BAO Jinsong, ZHANG Rong, LI Jie, LU Yuqian, PENG Tao Journal of Mechanical Engineering    2022, 58 (18): 103-115.   DOI: 10.3901/JME.2022.18.103 Abstract （829）      PDF（pc） （881KB）（736）       Knowledge map    Save Digital twin is playing an important role in manufacturing system. However, in the complex manufacturing scene for human-robot collaboration, human-robot-environment and its digital twin system show the characteristics of heterogeneous and complex tasks, dynamic environment and real-time interaction. At present, the research on intelligent methods in the digital twin collaboration process of human-robot-environment integration is poor, especially the transfer and reinforcement of digital twin model in collaboration, so as to meet the robustness and adaptive ability of manufacturing system. The paper puts forward the digital twin collaboration technology for human-robot-environment integration, and launches the scientific problem of human -robot integration in digital twin collaboration from the two cores of environment and task. Firstly, the digital twin model of collaborative assembly environment is given to provide understanding for human-robot-task interaction in the form of virtual assembly; Secondly, the corresponding spatial model and collaboration model are established to provide theoretical support for the twin collaboration of integration; Finally, taking the most typical human-robot integrated manufacturing scenario (assembly task) as an example, the transfer learning algorithm is used to provide assembly operation guidance for the robot at the decision-making level, and the reinforcement learning algorithm is used to optimize the specific execution actions of the robot. In different types of products, the corresponding human-robot collaborative assembly planning schemes can be generated, which proves the feasibility of the proposed method. Reference | Related Articles | Metrics | Comments（0）

Select

Type Synthesis of New Kinematic Bifurcation Parallel Mechanism Based on Atlas Method LI Yongquan, ZHENG Tianyu, JIANG Hongsheng, ZHANG Duo, ZHANG Lijie Journal of Mechanical Engineering    2022, 58 (23): 1-17.   DOI: 10.3901/JME.2022.23.001 Abstract （809）      PDF（pc） （16961KB）（789）       Knowledge map    Save The multi-mode parallel mechanism (PM) has great application prospects in aerospace, machining, medical rehabilitation and other fields. However, there are few types of kinematic bifurcation PMs that can realize multi-mode, and most kinematic bifurcation PMs contain RER branches with variable DOF. Therefore, a new type of kinematic bifurcation PM is synthesized based on the atlas method, and the mechanism contains four types of branch chains with variable DOF, which are different from the existing RER branches. Firstly, based on the atlas method, the 2T1R motion bifurcation PM is synthesized by taking the two instantaneous DOF lines at the initial position of the mechanism as an example, which are not coplanar and perpendicular to each other. Then, the direction of the R pair connected to the fixed platform by the URR branch neutralizing mechanism is changed, which made it have two DOFs properties of 2R2T and 3R1T. The improved URR branch chain configuration scheme is applied to some 4-DOF and 5-DOF chains. Three other types of variable DOF chains are proposed, with 4, 12 and 32 chains in each type. Based on the classification of four types of branch chains with different variable DOF in the mechanism, four types of new kinematic bifurcation PMs with 2T1R+2R1T two modes are synthesized, including 12 subcategories in total. Taking the fourth type of branched chain with variable DOF as an example, it is introduced into the PM, and a new type of kinematic bifurcation PM with 3T1R+2R2T two modes is synthesized by the atlas method. Reference | Related Articles | Metrics | Comments（0）

Select

Milling Tool Wear Prediction Research Based on Optimized PCANet Model DUAN Jian, ZHOU Hongdi, LIU Zhiyong, ZHAN Xiaobin, LIANG Jianqiang, SHI Tielin Journal of Mechanical Engineering    2023, 59 (1): 278-285.   DOI: 10.3901/JME.2023.01.278 Abstract （788）      PDF（pc） （443KB）（656）       Knowledge map    Save Milling tool wear condition affects real production. Thus, study on tool condition monitoring has great importance in engineering. Deep learning models, for example convolutional neural network, have been applied in tool condition monitoring during milling process. Yet the model interpretability is poor, and the prediction results vary a lot. As a novel variant of convolutional neural network, principal component analysis network (PCANet) model is well-explained. However, the self-supervised features extraction capacity still requires improvement, and few industrial cases have been studied. In order to address these problems, original PCANet model structure is optimized, then activated PCANet with max pooling and support vector regression (APCANet-MP-SVR) model is proposed to extract sensitive features in unsupervised way and predict tool wear accurately. In detail, tanh activation function is applied to improve model generalization capacity, and then max pooling layer is introduced for features selection to replace complex Hash encoding and spectrum process. In the end, support vector regression is utilized to predict current tool wear. Case has been further studied to validate the brilliant performance and industrial suitability of the proposed model. Reference | Related Articles | Metrics | Comments（0）

Select

Laser Micromachining of Heterogeneous Multi-layer Composite Materials:A Review ZHENG Lijuan, SUN Yong, XU Xiangqian, YU Juman, WANG Jun, WANG Chengyong Journal of Mechanical Engineering    2025, 61 (1): 305-325.   DOI: 10.3901/JME.2025.01.305 Abstract （787）      PDF（pc） （1108KB）（482）       Knowledge map    Save High-end printed circuit board is the typical heterogeneous multilayer composite material. The quality of microstructures such as holes, slots, circuits, and patterns directly determine the operational performance of electronic devices in semiconductors, aerospace, 5G/6G communications, and supercomputing. With the increasing complexity of printed circuit board materials and processing quality evaluation systems, the miniaturization of processing scales, and the high requirements for processing quality such as consistency and reliability, laser processing of high-end PCB is confronted with great challenges. This article provides a comprehensive review of the research progress in laser micromachining technology for heterogeneous multilayer composite materials. It systematically analyzes the technological changes brought about by new materials and extreme-scale structures in laser micromachining processes and identifies the technical challenges and future development directions. The aim is to provide guidance and reference for the manufacture of microstructures in high-end printed circuit boards through laser processing. Reference | Related Articles | Metrics | Comments（0）

Select

Research on NNBoost-based Uncertain Natural Frequency of Composite Laminates for Satellite Structures ZHAO Lin, LIU Yuan, CAO Xibin, HOU Yaodong, ZHANG Junjie Journal of Mechanical Engineering    2023, 59 (24): 242-250.   DOI: 10.3901/JME.2023.24.242 Abstract （779）      PDF（pc） （604KB）（346）       Knowledge map    Save In order to realize accurate analysis of the natural frequency of composite laminates for satellite structures, a method for analyzing the uncertainty of the natural frequency orthotropic composite laminates by using neural network boosting(NNBoost) model is proposed by considering the factors of uncertainty such as machining errors and material random deviations. In this paper, the NNBoost model is used as a surrogate model for solving and predicting the natural frequency. The objective function is set as sum of the loss function and the regularization term. In the solving process, a gradient descent method based on Taylor expansion is used to update the weights and thresholds to accelerate the convergence. Using this method, statistical characteristics of the natural frequencies of an orthotropic composite laminate are analyzed with the randomness of input parameters considered. The simulation results show that compared with the direct Monte Carlo simulation(MCS), the proposed method significantly improves the solution efficiency while ensuring the prediction accuracy. Compared with the traditional back propagation(BP) neural network method, the mean square error of the prediction results with this method is smaller than that of the BP neural network and the error convergence is more stable. Reference | Related Articles | Metrics | Comments（0）

Select

Research Progress on Energy Density of Li-ion Batteries for Evs YANG Xulai, YUAN Shuaishuai, YANG Wenjing, LIU Chuang, YANG Shichun Journal of Mechanical Engineering    2023, 59 (6): 239-254.   DOI: 10.3901/JME.2023.06.239 Abstract （775）      PDF（pc） （983KB）（808）       Knowledge map    Save The power battery is the source of driving energy for electric vehicles (EVs), which is directly related to driving range and the safety of EVs. So far, lithium-ion batteries(LIBs) have been extensively used as the power sources for EVs owing to the high energy density and long cycle-life. Based on the battery history and the LIB energy density data of more than 2 000 types of passenger EVs in the 1-48 Catalogs of new energy vehicles exempted from vehicle purchase tax of China, the evolution process of the LIB energy density increasing is systematically analyzed from the data in the Catalog. Meanwhile, the improvement of LIB energy density in China and its role in promoting the development of EVs are reviewed. Then, the advantages and disadvantages of the energy density enhancement technology for lithium-ion power battery are analyzed from the aspects of electrode material, battery process engineering and battery pack structure. Finally, based on the correlation between battery energy density and safety, the safety technologies of high energy density battery in design phase, manufacture phase and use phase of the whole cycle life are summarized, and the development trend of lithium-ion power battery is prospected, which can provide a reference for the healthy development of EVs. Reference | Related Articles | Metrics | Comments（0）

Select

Fundamentals and Prospects of Additive Friction Stir Deposition：Opportunities and Challenges SHEN Zhikang, LI Dongxiao, SUN Zhonggang, MA Liangchao, LIU Xiaochao, TIAN Yanhong, GUO Wei, HOU Wentao, PIAO Zhongyu, YANG Xinqi, LI Wenya Journal of Mechanical Engineering    2025, 61 (2): 56-85.   DOI: 10.3901/JME.2025.02.056 Abstract （768）      PDF（pc） （1718KB）（931）       Knowledge map    Save Integrative design and integrated manufacturing of major equipment’s’ large critical structure such as aeronautics, astronautics and weapons provide guarantees of lightweight manufacturing and service performance. As a transformative technology can achieve innovative structure, additive manufacturing has received extensive attention and being applied, nevertheless, additive manufacturing of lightweight and high-strength metals such as high strength aluminium alloy and magnesium alloy faces many challenges. Additive friction stir deposition provides a new thought and method for such kind metals, since its process involves strong plasticity and non-melting, which further facilitates the progress of solid-state additive manufacturing and equipment. Dominant advantages of additive friction stir deposition have aroused worldwide attention and investigation; However, this technology’s basic theory and deposited materials’ microstructure evolution and performance need to be clarified. Research progress in additive friction stir deposition was systematically summarized, domestic and foreign research achievements such as heat production mechanism, material flow behavior, design of printing tool, processing parameters, microstructure evolution and performance of additive friction stir deposition were comprehensively reviewed. Finally, future opportunities and development trends of additive friction stir deposition were pointed out. Reference | Related Articles | Metrics | Comments（0）

Select

Connotation, Architecture and Enabling Technology of Industrial 5.0 ZHUANG Cunbo, LIU Jianhua, ZHANG Lei Journal of Mechanical Engineering    2022, 58 (18): 75-87.   DOI: 10.3901/JME.2022.18.075 Abstract （763）      PDF（pc） （492KB）（1254）       Knowledge map    Save Industry 4.0 reinforces the highly transformative impact brought by digitization, data-driven and interconnected industries. However, it does not emphasize the importance of research and innovation in supporting industry to provide long-term services to mankind all over the world, nor does it solve the problems of how to use technological innovation to promote cooperation and “win-win” interaction between industry and society. Industry 5.0 systematically proposes to take industrial workers as the core of industrial production, so as to achieve social goals beyond employment and growth and steadily provide prosperity. Nevertheless, as a rethinking of the future industry development, Industrial 5.0 is still in its infancy with respect to research, and there are only few unsystematic research results presented. By reviewing the background of emergence of Industrial 5.0 and the history of the concept evolution, the paper analyzes the differences between Industrial 5.0 and Industrial 4.0, and summarizes four main characteristics of Industrial 5.0, including human-centric, sustainability, resilience and wisdom. Furthermore, we systematically explain the connotation of Industrial 5.0, and discuss the relationship between the concepts of industry 5.0 and society 5.0. Finally, we construct the three-dimensional architecture of Industrial 5.0, propose the enabling technologies of Industrial 5.0, and investigate the implementation approach of Industrial 5.0. Reference | Related Articles | Metrics | Comments（0）

Select

Review on the Key Technologies of Complex Surfaces Polishing Based on Robots DENG Jianxin, YUAN Bangyi, HUANG Qiulin, DING Dukun, XIN Manyu, LIU Guangming Journal of Mechanical Engineering    2024, 60 (7): 1-21.   DOI: 10.3901/JME.2024.07.001 Abstract （759）      PDF（pc） （703KB）（519）       Knowledge map    Save The polishing process is one of the important methods to enhance the surface quality of parts and precision. Complex curved surface polishing technology based on the industrial robot system, with the advantages of flexibility, small land occupation, high precision and low cost, is gradually mature and replacing the manual polishing and the grinding based on CNC machine tools. By analyzing the principle of grinding and polishing based on industrial robots, the key problems affecting the accuracy of robot grinding and polishing are introduced: the planning accuracy of the grinding and polishing process path and the force control accuracy. The former focuses on the balance between processing efficiency and accuracy, while the latter focuses on the accuracy and consistency of processing. From these two aspects, the research purposes, characteristics and achievements of machining path planning methods and compliance force control strategies for robotic grinding and polishing systems are summarized. The machining path planning of robot grinding and polishing system is mainly based on the application and improvement of the commonly used machining path planning methods in the CNC machine tool grinding and polishing, and there are a few machining path planning methods proposed according to the characteristics of the robot. The strategies of passive compliance, active (impedance control, force/position hybrid control) and intelligent control have proposed to address the force control challenges of grinding and polishing based on robots; their principle, research and application are compared and analyzed. After that, the possible future development directions are suggested. It provides a direction guidance for researchers in this field. Reference | Related Articles | Metrics | Comments（0）

Select

Design and Experiment of Intelligent Picking Robot for Famous Tea ZHOU Yujie, WU Qiang, HE Leiying, ZHAO Runmao, JIA Jiangming, CHEN Jianneng, WU Chuanyu Journal of Mechanical Engineering    2022, 58 (19): 12-23.   DOI: 10.3901/JME.2022.19.012 Abstract （735）      PDF（pc） （873KB）（1059）       Knowledge map    Save In view of the current situation of labor force shortage in famous tea picking, this paper designs a robot for famous tea picking, which is suitable for natural environment. The robot is composed of picking module, 3P-Delta manipulator, vision system and controlling system. The robot captures the image of tea canopy using RGB-D camera, and then calculates the picking points by deep learning model and the skeleton method. Based on the growth characteristics of famous tea, the picking trajectory model of the manipulator was established. The Bézier curve was used to optimize the picking path of tea, which effectively alleviated the acceleration mutation caused by the rapid motion of the manipulator and improved the smoothness of the picking movement. The dynamic model of the manipulator was established by using the principle of virtual work, and the picking control algorithm of the manipulator is designed based sliding surface variable structure control. The exponential reaching law in the control algorithm is optimized, so that the chattering phenomenon in the sliding surface control is effectively suppressed in the process of rapid reaching. The field test results show that the picking robot can realize the picking of famous tea in the natural environment, and the picking rate and integrity rate are 75.53% and 54.68%, respectively. The average picking speed of the robot is 0.451/s. Reference | Related Articles | Metrics | Comments（0）

Select

Remanufacturing Service Combination and Optimization for Generalized Growth of Retired Mechanical Products WANG Lei, GUO Yuyao, CAO Jianhua, ZHANG Zelin, XIA Xuhui, ZHAO Hui Journal of Mechanical Engineering    2023, 59 (7): 339-354.   DOI: 10.3901/JME.2023.07.339 Abstract （730）      PDF（pc） （77929KB）（326）       Knowledge map    Save Under the generalized growth-oriented remanufacturing services, the product-component-parts multi-level service objects and the upgrade, recovery and downgrade multi-granularity remanufacturing service requirements lead to the multiplication of service activities and the number of suppliers compared with traditional remanufacturing services. In this case, a remanufacturing service composition and optimization method was proposed to solve the complicated and difficult remanufacturing service composition and optimization process. Firstly, to quickly obtain multi-level and multi-granularity service scheme, remanufacturing service activities were described by semantics based on OWL-S, and service composition process was proposed to realize multi-level composition of service activities automatically. Secondly, to improve the combination and optimization efficiency of service providers, the rough-fuzzy number is used to analyze the coupling of service activities in service schemes and merge redundant service activities. Finally, to ensure the multi-party interests and environmental benefits of remanufacturing service, a remanufacturing service supplier portfolio optimization model was established with carbon emissions, time and cost as optimization objectives and solved by non-dominated ranking genetic algorithm. The feasibility and effectiveness of the proposed method were verified by taking a batch of retired manual gearbox as an example. Reference | Related Articles | Metrics | Comments（0）

Select

Review on Mechanism Design and Jumping Process Control of Jumpable Mobile Robots SONG Jingzhou, GONG Xinglong, DUAN Jiachen, ZHANG Tengfei Journal of Mechanical Engineering    2024, 60 (15): 1-17.   DOI: 10.3901/JME.2024.15.001 Abstract （730）      PDF（pc） （1119KB）（591）       Knowledge map    Save In recent years, mobile robots that combine traditional wheeled, legged, and jumping movements have received widespread attention from researchers. Their advantages in unstructured terrain make them have broad application prospects in emergency rescue, field inspections, underground exploration, and other fields. The current research status of new mobile robots such as wheeled jumping robots, wheeled leg jumping robots, and spherical jumping robots are all introduced in detail in the paper, and a comparative analysis also is conducted from their mechanism design and jumping control aspects. In terms of mechanism design, it analyzes the jumping mechanism design characteristics of wheeled, wheeled leg, and spherical jumping robots in recent years, and summarizes their structural design characteristics. In the section of jump control methods, the aerial attitude control methods and landing buffering control methods of jumping mobile robots were reviewed. Finally, from the aspects of structure, energy storage, intelligent control and so on, the future development direction and trend of jumping mobile robot are discussed and prospected. Reference | Related Articles | Metrics | Comments（0）

Select

Key Technologies and Research Progress of Brake-by-wire System for Intelligent Electric Vehicles ZHANG Qixiang, WANG Jinxiang, ZHANG Yihan, ZHANG Ronglin, JIN Liqiang, YIN Guodong Journal of Mechanical Engineering    2024, 60 (10): 339-365.   DOI: 10.3901/JME.2024.10.339 Abstract （726）      PDF（pc） （722KB）（490）       Knowledge map    Save Intelligent electric vehicles require the brake system to realize functions such as active braking and braking energy recovery, and traditional brake systems cannot meet the above requirements. The brake-by-wire system has the advantages of compact structure, rapid response, precise control, and strong compatibility. It is an ideal actuator for autonomous driving and has become a current research hotspot. To systematically and timely grasp the development trend of this field, the key technologies and research progress of the brake-by-wire system for intelligent electric vehicles are reviewed. The types and characteristics of the brake-by-wire system are introduced, and the development trend and research focus of the structural scheme of the brake-by-wire system are clarified. Then the typical products and characteristics of the brake-by-wire system are summarized, and the overall control architecture of the brake-by-wire system for an intelligent connected electric vehicle is proposed. On this basis, the key technologies such as testing and modeling of the brake-by-wire system, power cylinder pressure control, wheel cylinder pressure control, wheel cylinder pressure estimation, solenoid valve control, clamping force control, pedal feel simulation control, sensor fault diagnosis, and personalized control are sorted out. The vehicle's longitudinal motion control methods, such as anti-lock braking, adaptive cruise, and automatic emergency braking based on the brake-by-wire system, are summarized. Finally, the problems faced by the research on the brake-by-wire system for intelligent electric vehicles and the future development trend are analyzed and prospected. Reference | Related Articles | Metrics | Comments（0）

Select

Research Advance on Material Removal at Microscale towards Ultra-precision Manufacturing CHEN Lei, LIU Yangqin, TANG Chuan, JIANG Yilong, SHI Pengfei, QIAN Linmao Journal of Mechanical Engineering    2023, 59 (23): 229-264.   DOI: 10.3901/JME.2023.23.229 Abstract （720）      PDF（pc） （2549KB）（679）       Knowledge map    Save Ultra-precision manufacturing has been as the competitive frontier for most of coastal countries and regions with the incremental demands for ultra-high precision surfaces and structures in the hi-tech industrializations such as ultra-large-scale integrated circuits, microelectromechanical systems, and precise optics. The essence of ultra-precision manufacturing is to fabricate ultra-high precision surface or structure through the controllable addition, migration, or removal of the microscopic materials. This study reviewed the latest advances of several types of ultra-precision manufacturing technologies such as single point diamond turning, scanning probe lithography, chemical mechanical polishing, and ultra-precision grinding, which normally remove the materials at micro-scale under contact state. After that, the effects of processing parameters, processing tools, processing environment, and physical and chemical characteristics of the processed materials themselves on the material removal at microscale were systematically summarized and the microscale removal models matched the different dominated mechanisms were reviewed. Final, the challenges that will be encountered in the future development of ultra-precision manufacturing to achieve the controlled material removal at the atomic scale were prospected. Reference | Related Articles | Metrics | Comments（0）

Select

Kinematic Performance Analysis of Spatial 2-DOF Redundantly Actuated Parallel Manipulator WANG Shijie, FENG Wei, LI Tiejun, ZHANG Jianjun, YANG Dong, LIU Jinyue Journal of Mechanical Engineering    2022, 58 (23): 18-27.   DOI: 10.3901/JME.2022.23.018 Abstract （714）      PDF（pc） （92688KB）（952）       Knowledge map    Save Aiming at the demand of high-performance manipulators in the field of construction robots, a spatial 2 rotational DOF 3-UPS&U redundantly actuated parallel manipulator is proposed. Based on the screw theory and the modified G-K formula, the overall degree of freedom of the manipulator is analyzed, and the kinematic characteristics of the universal joint rotation around the proper-constraint branch chain are determined. The mapping relationship between the actuated parameters and the end-point parameters is established, and the workspace is obtained. Through independent modeling of the actuated legs and the passive leg, the complete generalized Jacobian matrix of the parallel manipulator is constructed, and the dimensionless Jacobian matrix of the linear velocity of the end center point and the actuator joints is further obtained. The dexterity, load-carrying capacity and stiffness performance evaluation indexes of the manipulator under a specific workspace are established. The final results show that when the 3-UPS&U redundantly actuated parallel manipulator swings up and down at a high frequency, it has better comprehensive kinematic performance in the direction of the corresponding axis of the constraint branch, and can greatly reduce the amplitude of performance degradation. Reference | Related Articles | Metrics | Comments（0）

Select

Analysis and Verification on Working Principle of a New Deployable Mobile Robot Based on Rigid Origami YANG Fufu, LU Shuailong, SONG Yaqing, ZHANG Jun, YAO Ligang Journal of Mechanical Engineering    2022, 58 (23): 75-87.   DOI: 10.3901/JME.2022.23.075 Abstract （712）      PDF（pc） （1206KB）（855）       Knowledge map    Save Aiming at the problem that the body of the existing wheeled robot is relatively fixed and cannot adapt to the complex environment, a new type of deployable mobile robot mechanism is proposed by introducing a rigid origami mechanism, which is with less degrees of freedom and large folding ratio, into efficient wheeled motion, and improves the passing performance in complex environments. The working principle analysis of this mechanism is carried out, and the relationship between the three-dimensional sizes of the robot and driving angles is obtained. By establishing a simplified model of the robot, its dynamics is carried out. Then, the change of the driving torque of different positions with the driving angle is obtained, which is used to optimize the driving arrangement scheme. Through a proposed algorithm, the compatible movement between the main body folding and the wheel motion is realized, so that the robot can move efficiently in the complex environment. Finally, a physical prototype and the control system are built, based on which the movement and folding performance are verified through two experiments. The results show that the robot could fit complex paths flexibly by switching its postures, and has the advantages of large deployment and folding ratio. Therefore, the robot owns the potential applications in some engineering fields such as detection, detection and rescue. Reference | Related Articles | Metrics | Comments（0）

Select

Repairing Deteriorated Data of Wind Turbines by Multi-head Attention Bi-directional Long Short Time Memory Networks under Complex Working Conditions YU Xiaoxia, TANG Baoping, WANG Weiying, WU Xuanyong, LI Biao Journal of Mechanical Engineering    2023, 59 (14): 1-9.   DOI: 10.3901/JME.2023.14.001 Abstract （703）      PDF（pc） （1048KB）（725）       Knowledge map    Save To address the problem of low early warning accuracy of condition monitoring models due to a large number of missing data in wind turbine monitoring parameters under variable speed and variable load, multi-headed attention bidirectional long and short-term memory networks (MA-BiLSTM) is proposed for repair those data. The multi-headed attention machine is used to suppress the interference of variable loads on the neural network feature extraction under complex working conditions. In addition, the model feature extraction ability is increased by constructing a cross-layer of residual units, and the hidden features of existing monitoring data and the correlation between multi-source parameters are fully learned. The Bi-LSTM cells are used to simultaneously learn the law of the monitoring data of wind turbines to achieve the prediction and repair of incomplete data. The application results show that the proposed MA-BiLSTM networks can suppress the multivariate load disturbance under complex working conditions and realize the repair of incomplete data for improving fault detection accuracy of wind turbines. Reference | Related Articles | Metrics | Comments（0）