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    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
    Abstract1360)      PDF(pc) (852KB)(1186)       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.
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    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
    Abstract1269)      PDF(pc) (920KB)(1529)       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.
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    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
    Abstract838)      PDF(pc) (587KB)(460)       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.
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    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
    Abstract787)      PDF(pc) (1108KB)(482)       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.
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    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
    Abstract768)      PDF(pc) (1718KB)(931)       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.
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    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
    Abstract730)      PDF(pc) (1119KB)(591)       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.
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    Cognitive Empowerment for Human-robot Collaboration: Research Progress and Challenges
    KOU Yiqun, YANG Ye, LIU Jie, HU Youmin, LI Lin, YU Baichuan, XU Jiahe, HU Zhongxu, SHI Tielin
    Journal of Mechanical Engineering    2025, 61 (3): 1-22.   DOI: 10.3901/JME.2025.03.001
    Abstract625)      PDF(pc) (612KB)(608)       Save
    In the transition from Industry 4.0 to Industry 5.0, a human-centered approach has gradually emerged as a focal point in the field of smart manufacturing. Current human-machine collaboration not only emphasizes technological advancements and efficiency improvements but also stresses the integration of human higher-order cognitive thinking with machine computational capabilities to achieve cognitive empowerment. Based on this premise, this study reviews existing research on cognitive empowerment in human-machine collaboration, focusing on key areas such as interactive perception, task planning and execution, and skill learning. The challenges of multimodal information integration, task reasoning, dynamic decision-making, and skill knowledge representation are highlighted. Furthermore, methods are proposed to support human-machine cognitive using knowledge graph construction technologies, as well as to optimize tasks and facilitate dynamic decision-making in complex environments through the application of knowledge graph reasoning techniques. Building upon an analysis of the limitations in current research on cognitive empowerment in human-machine collaboration, this study also forecasts the future directions for deep cognitive collaboration within intelligent manufacturing environments.
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    Design and Motion Analysis of Flipping Robot Based on Yoshimura Origami Structure
    TAN Kangning, ZHANG Qiwei, HE Zihan, MEI Dong, TANG Gangqiang, FANG Hongbin, WANG Yanjie
    Journal of Mechanical Engineering    2025, 61 (1): 101-113.   DOI: 10.3901/JME.2025.01.101
    Abstract625)      PDF(pc) (936KB)(328)       Save
    With the advantages of excellent deformation ability and easy assembly, origami structure has a wide application prospect in soft robot design. Based on the excellent bending and deformability of Yoshimura origami structure, a multi-degree of freedom flipping soft robot is proposed. Firstly, a pneumatic origami actuator composed of the pneumatic muscle and the Yoshimura origami structure is designed, and the number of the pneumatic muscle segments is optimized by analyzing the bending performance of the actuator. Then, based on the design concept of modularization and integration, a prototype of the flipping robot composed of double pneumatic origami cells is built. The kinematic model of the robot is established, and the trajectory planning theory of the flipping robot in two-dimensional plane coordinate system is proposed. The four kinds of periodic gaits of straight, side, arch and mouth, and the interpolation trajectory of straight line and arc are analyzed. Finally, the experimental test results show that the robot has good motion performance, and successfully verified four basic motion gaits and trajectory interpolation motions in the horizontal plane. The maximum speed of the robot can reach 77.19 mm /s, and it can realize one-way flipping and climbing on the 30° slope surface, and has the ability of discontinuous and transitional surface motion.
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    Respiration Measurement Technology Based on Inertial Sensors:A Review
    FANG Xudong, DENG Wubin, WU Zutang, LI Jin, WU Chen, MAEDA Ryutaro, TIAN Bian, ZHAO Libo, LIN Qijing, ZHANG Zhongkai, HAN Xiangguang, JIANG Zhuangde
    Journal of Mechanical Engineering    2024, 60 (20): 1-23.   DOI: 10.3901/JME.2024.20.001
    Abstract528)      PDF(pc) (870KB)(404)       Save
    With the increasing demand for disease prediction and diagnosis, scientific and technological innovation for people’s life and health has become an urgent need, and wearable equipment for monitoring physiological signals has attracted more and more attention. Respiration is an important parameter that reflects the physiological state of the human body. For example, major diseases such as pneumonia, sleep apnea syndrome, and pulmonary embolism are often accompanied by changes in human respiratory parameters. Monitoring respiratory parameters can effectively predict and diagnose related diseases, but corresponding wearable monitoring technology has yet to make significant progress. Due to the advantages of low invasiveness and light weight, inertial sensors are very suitable to be developed into wearable devices for monitoring breathing signals. Firstly, starting from the development processes of respiration monitoring with inertial sensors, and discusses in detail the four development stages of respiration monitoring with inertial sensors (respiration waveform extraction, apnea recognition, sleep posture recognition, and respiration monitoring when walking and running), the methods of respiration monitoring with inertial sensors, and the approaches of sensor data processing. Secondly, a comparative analysis of different stages of respiration monitoring by inertial sensors is carried out, and the advantages and disadvantages of different methods are described in detail. Thirdly, the challenges and future development directions of inertial sensors for monitoring respiration are summarized and prospected. Finally, some suggestions and predictions are made for the development of wearable respiratory monitoring devices based on inertial sensors.
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    Slip-aware Adaptive Trajectory Tracking Control Strategy for Autonomous Tracked Vehicle
    WU Yang, WANG Cong, DONG Guoxin, ZENG Riya, CAO Kai, CAO Dongpu
    Journal of Mechanical Engineering    2024, 60 (24): 211-225.   DOI: 10.3901/JME.2024.24.211
    Abstract501)      PDF(pc) (1089KB)(475)       Save
    Due to the variable working environment and complex track-ground contact mechanism, it is difficult to establish an accurate dynamic model for tracked vehicles. Moreover, affected by the drastic impulse from the unstructured road surface, the accurate information of velocity is usually difficult or costly to measure. These unfavorable factors bring challenges to the trajectory tracking control of tracked vehicles. Aiming at the difficulty in modeling dynamics, a hybrid kino-dynamic model with track rotation acceleration as virtual control input is established, and generalized disturbances are used to describe the uncertainty caused by track slip. To deal with the unmeasurable velocity information, an extended state observer (ESO) is designed based on the hybrid model, and the state estimation of the whole vehicle is realized using only GNSS signals and track encoder signals. Finally, taking the rotational acceleration of the track as the intermediate control input, a hierarchical disturbance-rejecting control strategy consisting of an upper layer path tracking controller and a lower layer track speed controller is designed. Simulation and test results show that the proposed state observation and control strategy can accurately estimate the real-time velocity of the tracked vehicle, and effectively improve the path tracking accuracy under external disturbances.
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    Dynamic Vision Enabled Contactless Intelligent Machine Transfer Diagnosis Method
    LI Xiang, CHEN Xinrui, LEI Yaguo, LI Naipeng, YANG Bin, YU Shupeng
    Journal of Mechanical Engineering    2024, 60 (24): 1-10.   DOI: 10.3901/JME.2024.24.001
    Abstract468)      PDF(pc) (591KB)(337)       Save
    Vibration monitoring and signal processing are crucial methods for machine fault diagnosis. Currently, the popular contact vibration measurement method has achieved significant results. However, such methods have high requirements for deployment environments, and are not suitable for many engineering scenarios. Therefore, contactless methods for vibration monitoring and fault diagnosis are gaining increasing attention. Event-based camera is a bio-inspired contactless dynamic visual sensor with extremely high temporal resolution, high dynamic range, and low data redundancy, which can capture mechanical micro-vibrations from a visual perspective. This paper proposes a contactless machine intelligent transfer diagnosis method enabled by dynamic vision. An event-based camera is used to capture the dynamic visual vibration signals of machines. A cross-domain diffusion generation model of dynamic visual data is established, enabling the intelligent generation of visual data in unknown fault states in testing scenarios. A novel intelligent method for processing dynamic visual data and recognizing machine fault patterns is proposed based on the neuromorphic computing framework, achieving cross-domain intelligent transfer diagnosis effect. The proposed method has been validated on a nuclear power plant pump circulation test bench. The results show that the proposed method is able to achieve intelligent transfer diagnosis of machines based on dynamic visual data, and provides an effective and promising solution for vibration measurement and fault diagnosis in engineering scenarios in the perspective of vision.
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    Analysis on Carbody Vertical Abnormal Vibration Characteristics and Causes of Light Rail Transit
    WANG Qunsheng, ZENG Jing, WEI Lai, JIANG Xuesong, CHEN Shaoqiang
    Journal of Mechanical Engineering    2024, 60 (20): 208-216.   DOI: 10.3901/JME.2024.20.208
    Abstract468)      PDF(pc) (499KB)(202)       Save
    Carbody vertical abnormal vibration of light rail transit during operation seriously impact the passengers’ ride comfort. To address this issue, carbody vertical vibration characteristics of light rail transit is studied through field test, theoretical analysis and simulation reproduction and the causes of abnormal vibration are clarified. The results show that the carbody vertical vibration frequency with 7.5 Hz is the main reason for the deterioration of the light rail transit ride comfort. The trailer of the light rail transit exhibits a vibration mode of floating up and down, while the adjacent vehicles pitch in the opposite direction. The frequency of carbody pitching motion is significantly affected by the longitudinal stiffness of the elastic articulation, while the secondary vertical stiffness of the bogie and the longitudinal deviation from carbody gravity to the bogie have a minor impact. The insufficient stiffness of the elastic articulation is the preliminary cause, with a measured hinge stiffness of 11.87 MN/m, which is far below the design value. A simulation model based on the measured data reproduces the carbody abnormal vibration and confirms that the insufficient longitudinal stiffness of the elastic articulation is the root cause. This relevant research provides technical support for addressing abnormal vibration problems and enhancing the performance of light rail transit.
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    Review on Biomimetic Micro/nanostructured Surfaces and Their Manufacturing Techniques for Drag Reduction
    CUI Xianxian, DU Hanheng, CHEN Huawei
    Journal of Mechanical Engineering    2025, 61 (9): 1-22.   DOI: 10.3901/JME.2025.09.001
    Abstract460)      PDF(pc) (3075KB)(449)       Save
    Drag reduction surfaces have been receiving increasing attention in various fields such as aviation, aerospace, and maritime due to their significant role in reducing energy consumption. And achieving high-efficiency drag reduction is significant. After hundreds of millions of years of natural selection, animals and plants in nature have developed numerous drag-reduction surfaces. The biomimetic micro/nanostructured surfaces by studying drag-reduction organisms, such as sharks, offer an innovative approach for efficient drag reduction. This review systematically summarizes the research progress of biomimetic micro/nanostructured surfaces for drag reduction and elucidates the morphological features and drag reduction mechanisms of shark-inspired surfaces and other fish-inspired surfaces. This work also describes the machining methods for biomimetic micro/nanostructured drag-reduction surfaces, including high-energy beam machining, surface etching, ultra-precision machining, 3D printing, and bio-replication technologies. Furthermore, it briefly outlines the practical applications of existing biomimetic drag-reduction surfaces in aerospace, sports events, pipeline transportation, and other areas. Finally, based on the analysis and summary of research progress, manufacturing methods, and practical applications, this study discusses the prominent advantages of biomimetic micro/nanostructured drag-reduction surfaces. It highlights the current status and challenges of machining technologies.
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    High-sensitive Magnetic Field Sensor Based on Terfenol-D and Fiber Bragg Grating
    HE Chaojiang, LI Peng, HE Cunfu, WANG Yujue, LIU Xiucheng
    Journal of Mechanical Engineering    2025, 61 (8): 1-8.   DOI: 10.3901/JME.2025.08.001
    Abstract414)      PDF(pc) (460KB)(363)       Save
    Traditional magnetic field sensors are susceptible to environmental electromagnetic interference, which is difficult to be applied to magnetic nondestructive testing under complex working conditions. Hence, a magnetic field sensor based on Terfenol-D and fiber grating is developed, and a sensor sensitivity enhancement method based on static bias magnetic field tuning is proposed. Firstly, based on the magnetostriction and fiber grating sensing theory, a Terfenol-D based fiber grating magnetic field sensor model is established, and the relationship between the wavelength shift of the fiber grating and the applied magnetic field strength of the Terfenol-D material is analyzed. Secondly, a static bias magnetic field is introduced to pre-magnetize the Terfenol-D material to adjust the detection sensitivity of the sensor to magnetic field changes. The theoretical analysis and experimental test results show that the magnetic field detection sensitivity of the sensor can be effectively improved to 9.38 pm/mT by the tuning of the static bias magnetic field, which is about 8.55 times compared with that of the unoptimized one. Finally, the optimized fiber grating magnetic field sensor based on Terfenol-D is applied to the magnetic leakage detection of steel plate, which not only realizes the defect localization and the quantitative characterization of the defect depth, but also shows better antimagnetic interference ability than that of the traditional Hall sensor.
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    Research Progress and Development Trends in Key Technologies of Large-scale Rigid-flexible Coupling Robots
    ZI Bin, ZHAO Jiahao, WANG Wei, DU Jingli, YANG Guilin
    Journal of Mechanical Engineering    2024, 60 (23): 21-42.   DOI: 10.3901/JME.2024.23.021
    Abstract410)      PDF(pc) (748KB)(326)       Save
    In large-scale and complex environments, automation and intelligent operations are of paramount importance in high-end manufacturing, aerospace, and major national projects. And they represent the level of innovative technology in the national manufacturing industry. Large-scale rigid-flexible coupling robots are primarily designed for complex operations in a large-scale environment, combining both rigid and flexible driven characteristics. These robots exhibit high levels of motion flexibility and mechanism adaptability in extensive, large-scale environments. Their emergence and development rely on the interdisciplinary fusion of mechanics, new materials, dynamics, and intelligent control. Focusing on the core theories and key technologies of large-scale rigid-flexible coupling robots, an overview of current research achievements in areas including the driving mechanisms and mechanism design, system modeling and performance analysis, as well as control and motion planning for large-scale rigid-flexible coupling robots are presented. Additionally, the typical applications of these robots in engineering are summarized, and the fundamental theory and key technologies for the future development trends of large-scale rigid-flexible coupling robots are reviewed and forecasted.
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    From Robot to Micro/nanorobot: Changes Not Only Dimensions
    LI Longqiu, LIU Junmin, ZHUANG Rencheng, CHANG Xiaocong, ZHOU Dekai
    Journal of Mechanical Engineering    2024, 60 (23): 1-20.   DOI: 10.3901/JME.2024.23.001
    Abstract393)      PDF(pc) (962KB)(313)       Save
    With the wide application of robotics in industrial, healthcare, service, education and military fields, the traditional macro-robotics technology is gradually unable to meet the growing demand for miniaturization, refinement and highly integrated functions. As an emerging branch in the field of robotics, micro/nanorobots (MNRs) have become a hotspot and frontier of research because of their micro size, large thrust-to-weight ratio, good controllability and strong expandability. By reviewing the development history of robotics, the four stages of robot development and five generations of power conversion are analyzed in detail, and the technical characteristics that robots should have are summarized. On this basis, the development history, connotation and technological stage of MNRs are discussed in-depth, focusing on the analysis of the fundamental changes from macro robots to MNRs in terms of medium environment, drive mode, transport mode and multifunctional coupling mode and other technical characteristics, as well as the technological challenges brought about by these changes. In particular, the advanced changes of MNRs are discussed in detail from four aspects, namely, design, manufacturing, control and testing. Finally, future directions and suggestions for the development of MNRs are presented. By exploring these issues in detail, theoretical guidance and practical basis are provided for the development of future robotics technology. It is expected that MNRs technology can achieve breakthroughs in more fields, provide new technical solutions for precision medicine, environmental governance, micro-and nanomanufacturing, etc., and promote the continuous progress of society and science and technology.
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    Thermal Error Modeling Method towards Electric Spindles Based on Digital Twin and Deep Transfer Learning
    MA Shuai, LENG Jiewu, CHEN Zhuyun, LI Weihua, LI Bo, LIU Qiang
    Journal of Mechanical Engineering    2025, 61 (3): 52-66.   DOI: 10.3901/JME.2025.03.052
    Abstract390)      PDF(pc) (1265KB)(387)       Save
    Thermal error is one of the main sources of electric spindle system errors, and thermal error modeling is an important means to improve system reliability. In machining scenarios where the electric spindle is loaded with tools, it needs to move in multiple directions, which makes real-time measurement difficult and difficult to collect sufficient thermal error samples. Furthermore, the data distribution under different working conditions presents large discrepancies, and a well-trained model under one working condition failed to obtain satisfactory prediction accuracy when applied to another working condition. To address these issues, a thermal error modeling approach based on digital twins and deep transfer learning is proposed. Firstly, a digital twin model of the thermal behavior of the electric spindle system is established, where the temperature fields and thermal deformation data under different working conditions can be simulated to alleviate the limitation of the scarcity of the thermal error samples in real scenarios. Secondly, a convolutional bidirectional long short-term memory network based on the domain adversarial mechanism is developed. The virtual data generated by the digital twin model is used as the source domain, and the real data is used as the target domain. Convolutional layers of different scales are used as the feature extractor to extract the spatial features of the temperature data from both the source and target domains so as to address the collinearity issue of multi-dimensional temperature features. The bidirectional long short-term memory network is constructed as a predictor to process the time-series relationship between temperature and thermal error and output predictions. Additionally, the adversarial training technique of domain adaptation is employed to confuse the two domain features and minimize the distribution discrepancies between both domains, thereby improving the model's generalization ability. Finally, a multi-source data collaborative collection platform is established to obtain real data under variable working conditions. Different transfer tasks are constructed to validate the proposed method and the results showed the proposed method successfully achieves thermal error modeling in the absence of labeled thermal error samples and exhibits good prediction performance.
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    Review of Micro-bionic Robots
    LUO Zirong, HONG Yang, JIANG Tao, LIN Zening, YANG Yun, ZHU Qunwei
    Journal of Mechanical Engineering    2025, 61 (3): 178-196.   DOI: 10.3901/JME.2025.03.178
    Abstract389)      PDF(pc) (841KB)(363)       Save
    As a micro-electromechanical system with a size of centimeters or below, micro-bionic robots have the characteristics of small size, light weight and excellent portability. They are widely used in complex environments such as environmental detection, target search, reconnaissance and strike. In order to enable researchers to understand the research progress of micro-bionic robots, a summary and analysis of relevant literature in the past 15 years are conducted based on the world’s largest abstract and citation database Scopus, providing a visual depiction of the development trends in the field of micro-bionic robots. The general characteristics and research status of micro-bionic robots are summarized from the three key points of the bionic movement form, manufacturing technology and driving technology of micro-bionic robots, supplemented by the introduction of the special research direction of bio-electromechanical hybrid micro robots. The technical bottleneck of the development of micro-bionic robots is fully analyzed, and the development idea of energy-driving-sense-control full flexible integration is put forward, which promotes the innovative development of integrated manufacturing technology. Based on the military and anti-terrorism and riot control application background, the characteristics and advantages of micro-bionic robots are fully analyzed, and the combat application conception with micro-bionic robots as the core is carried out. In addition, the application of micro-bionic robots in civil life is discussed. Finally, the shortcomings and future development of the existing micro-bionic robots are discussed and summarized, which provides a valuable reference for the development of the micro-bionic robots technology and its military application prospect.
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    Cross-domain Emerging Fault Diagnosis of Rotating Machinery Using Source-free Self-supervised Domain Adaptation Network
    YUE Ke, LI Jipu, CHEN Zhuyun, HE Guolin, DENG Shuhan, LI Weihua
    Journal of Mechanical Engineering    2025, 61 (3): 67-76.   DOI: 10.3901/JME.2025.03.067
    Abstract381)      PDF(pc) (517KB)(237)       Save
    With the rapid advancement of next-generation artificial intelligence technologies, data-driven intelligent fault diagnosis methods have found widespread applications in mechanical equipment. High-precision diagnosis of intelligent diagnostic models typically relies on a large volume of labeled data. However, unpredictable new faults may occur during the operation of mechanical equipment, which makes it difficult to adopt the model trained on known samples to accurately identify newly occurring faults. Furthermore, data privacy restricts the accessibility of data, adding substantial complexity to the domain adaptation process for diagnostic models. To address these challenges, a source-free self-supervised domain adaptation network is proposed for cross-domain emerging fault diagnosis of rotating machinery, which enables diagnosis emerging fault in target domain without access to source domain. First, a source domain fault diagnosis model is established using labeled source samples. Subsequently, a self-supervised pseudo-labeling technique based on uncertainty information entropy is utilized to acquire a target domain dataset with high-quality pseudo-labels. Finally, we merge the pseudo-labeled fault dataset with unlabeled fault dataset, then train the model through an adversarial training strategy to realize emerging fault detection. The effectiveness of the proposed method is validated through experiments conducted on an automotive gearbox dataset. Experimental results show that the proposed method can accurately detect emerging faults while maintaining the performance in classifying known fault types.
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    Survey of Predictive Cruise Control for Vehicle Platooning
    CHU Duanfeng, LIU Hongxiang, GAO Bolin, WANG Jinxiang, YIN Guodong
    Journal of Mechanical Engineering    2024, 60 (18): 218-246.   DOI: 10.3901/JME.2024.18.218
    Abstract366)      PDF(pc) (947KB)(235)       Save
    Vehicle platoon cruise control is mainly based on local limited traffic environment information. However, high uncertainty of the environment can affect vehicle modeling accuracy and control performance. As an evolution of cruise control, predictive cruise control has become a current research hotspot. In order to comprehensively analyze the research progress of vehicle platoon predictive cruise control, there are summarized four aspects, i.e., traffic environment information prediction, platoon motion behavior decision-making, vehicle trajectory planning, and vehicle trajectory tracking control. Firstly, it is introduced the research progress of vehicle platoon prediction of traffic environment information, including geography and traffic information of its road ahead through vehicle-infrastructure cooperation, and predicting motion states of surrounding vehicles through on-board sensors. The status quo and its trends of trajectory prediction methods based on deep learning are mainly introduced; Secondly, it is introduced the progress of decision-making of cooperative vehicle motion behaviors, while emphatically introducing the important roles of game theory and machine learning in this field, and pointing out trends of motion behaviors decision-making using the combined optimization with physical model and data; Thirdly, aiming at the problem of vehicle cooperative trajectory planning, current researches are sorted out from the perspectives of model-driven and data-driven, while advantages of reinforcement learning in collaborative trajectory planning are illustrated; Then, the problem of vehicle trajectory tracking control is expounded from two aspects of predictive cruise control and vehicle tracking control, respectively, while it is pointed out that the vehicle control method jointly driven by model and data has great application potential; Finally, the status quo and shortcomings of vehicle platoon predictive cruise control are summarized, and future trends in this field are prospected to provide new ideas for its application.
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    Sensorless Cutting Force Monitoring Based on Recurrent Neural Network
    CHENG Yinghao, LIU Changqing, ZHUANG Qiyang, LI Guangxu, HAO Xiaozhong
    Journal of Mechanical Engineering    2025, 61 (6): 14-23.   DOI: 10.3901/JME.2025.06.014
    Abstract365)      PDF(pc) (940KB)(317)       Save
    Cutting force is highly sensitive and capable of rapid response to changes in cutting state, which is considered as the most valuable physical quantity for machining state monitoring and adaptive machining. Since there is no need to introduce additional sensing components, an online prediction cutting force solution based on inherent servo monitoring signals in CNC systems has the potential to achieve long-term, low-cost, and accurate monitoring of cutting force. However, the relationship between servo monitoring signals and cutting force is very complex. Therefore, a cutting force online prediction method based on recurrent neural networks is proposed. Firstly, the problem of feed-axis cutting force prediction based on machine tool servo signals is defined as a nonlinear dynamic system modeling problem with adaptive time delay. Then, two types of recurrent neural networks, long short-term memory neural network (LSTM NN) and gated recurrent unit neural network (GRU NN), are introduced to directly learn the dynamic prediction model from end-to-end observation data. A set of variable speed hole milling experiments are carried out to construct a cutting excitation dataset under time-varying working conditions for comparative verifications. For the X-axis with more complex dynamic characteristics, LSTM NN has better prediction performance, with a relative root mean square error of 17.62%. For the Y-axis with relatively more simple dynamic characteristics, GRU NN has better prediction performance, with a relative root mean square error of 11.74%.
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    Sagittal Walking Control of Biped Robot Equipped with Artificial Tendon
    GAO Haibo, WANG Shengjun, SHAN Kaizheng, HAN Liangliang, YU Haitao
    Journal of Mechanical Engineering    2024, 60 (15): 18-27.   DOI: 10.3901/JME.2024.15.018
    Abstract362)      PDF(pc) (949KB)(251)       Save
    To overcome the shortage of elastic elements in rigid leg in traditional bipedal robots, a novel leg scheme with artificial tendon inspired from tendon-muscle complex in human’s leg and foot. A 4-DoF biped prototype with five-linkage configuration is also developed. The optimization paradigm of bipedal walking is constructed based on the linear inverted pendulum (LIP). The dynamical walking controller is devised based on the LIP model embodying the swing and the stance part. In swing, a PD control strategy is employed by combining the Bezier spline-based foot trajectory planning and model-based feedforward compensation. In stance, a control strategy with the feedforward of ground reaction force is proposed by integrating the feedback control of body pitch and height. The effectiveness of the proposed algorithm is experimentally validated. Experimental results demonstrate that the bipedal robot achieves stable walking at 0.8 m/s (almost 2 times of leg length per second), and the fluctuations of the body pitch and height are restrained within ±7° and ±4 cm, respectively. The aforementioned contributions can be further extended to the systematic design of humanoids executing mobile manipulation in 3D world.
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    New Contact Force Model and Experiment of Revolute Joints with Clearance in the Variable Stator Vane Mechanism
    ZHANG Hongwei, LUO Zhong, XU Chunyang, CHANG Jing, YAO Sibo
    Journal of Mechanical Engineering    2025, 61 (1): 1-12.   DOI: 10.3901/JME.2025.01.001
    Abstract358)      PDF(pc) (942KB)(300)       Save
    A new continuous contact force model considering conformal contact is proposed to address the issue of inaccurate calculation of dynamic contact force for revolute joints with small clearance in the variable stator vane (VSV) mechanism of aero engines. Firstly, the elastic contact force model is modified based on the improved Winkler contact theory. On this basis, a new continuous contact force model for small clearance revolute joints is proposed by incorporating the damping dissipation term from the Flores model, which has a wide range of applicability for the restitution coefficient. Then, the applicability of the proposed contact force model is analyzed under different contact lengths, restitution coefficients, clearance values and initial collision velocities, and compared with traditional contact force models such as L-N model. Finally, the proposed contact force model is applied to the dynamic calculation of the clearance revolute joint of the VSV mechanism. A VSV mechanism principle-level experimental platform is designed for experimental verification. The results indicate that the dynamic numerical calculation based on the new model can accurately reflect the contact characteristics of the clearance joint and the dynamic response of the mechanism, verifying the effectiveness of the proposed contact model.
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    Multifunctional Parallel Six-wheel-legged Rescue Robot
    LIU Shangfei, WANG Junzheng, LIU Dongchen, ZHAO Jiangbo, SHEN Wei, WANG Shoukun
    Journal of Mechanical Engineering    2024, 60 (21): 14-26.   DOI: 10.3901/JME.2024.21.014
    Abstract357)      PDF(pc) (1045KB)(219)       Save
    In response to the demand for highly mobile, large payload and long duration mobile robot platforms for major natural disaster rescue missions, a multifunctional parallel six-wheel-legged rescue robot is proposed. A leg structure with pneumatic balance transmission linkages is designed to enhance load capacity. A power system using a combination of high-power-density batteries and a gasoline engine generator is adopted to improve endurance. A 7-degree-of-freedom manipulator is equipped to handle various tasks such as transportation and demolition. An environment perception platform incorporating multiple sensors and a remote operation control platform based on 5G communication network are built to enable remote human-robot interaction control. Both walking and driving locomotion modes are designed to satisfy the robot's basic motion requirements. Specifically, a variable body height and variable support surface wheel-legged compound locomotion mode is designed to tackle complex and harsh terrain conditions. A posture-stabilizing optimal controller is developed based on the robot's body dynamics model, working in conjunction with body height controller and foot force tracking controller to achieve active vibration isolation control during wheel-legged compound locomotion. The energy-saving effect of the pneumatic balance transmission linkages is validated through energy-saving tests. Obstacle crossing, trench crossing, and active vibration isolation experiments are conducted to validate the robot's capability in overcoming obstacles, stability on slopes and rugged terrains. These experiments lay the foundation for the robot to cope with harsh environments in disaster areas and accomplish rescue tasks.
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    Advances in Interpretable Machine Degradation Assessment Optimization Models Based on Spectral Amplitude Fusion Aided Generalized Health Indices
    YAN Tongtong, WANG Dong, PENG Zhike, LEI Yaguo
    Journal of Mechanical Engineering    2024, 60 (18): 1-16.   DOI: 10.3901/JME.2024.18.001
    Abstract347)      PDF(pc) (835KB)(233)       Save
    Since health indices required for machine full lifecycle degradation assessment have problems such as cumbersome construction process, difficulty in explaining model construction and learning weights physically, insignificant separability and monotonicity of degradation trends, and difficulty in synchronously implementing machine condition monitoring, early fault diagnosis, and degradation assessment, research progresses of interpretable machine degradation assessment optimization models based on spectral amplitude fusion aided generalized health indices in recent years are summarized and two kinds of typical interpretable generalized health index weight optimization models based on degradation properties and fault feature sparsity and their application effects are explored. The core idea of this type of optimization models is to define the weighted sum of spectral amplitudes (such as amplitudes in the frequency domain or the envelope spectral domain) as a generalized health index, and then derive various generalized health index weight convex optimization models based on the degradation properties such as separability and monotonicity, as well as the sparsity properties of fault features. Compared with existing models, the proposed interpretable machine performance degradation assessment optimization models based on spectral amplitude fusion aided generalized health indices has the following characteristics:① only the commonly used Fourier transform or Hilbert transform in engineering are required as raw data preprocessing methods, avoiding the use of complex signal processing algorithms and parameter optimization processes; ② the construction of generalized health index weight convex optimization models comes from the convex optimization description of degradation properties and the sparsity description of fault features, so various weight optimization models have interpretability and unique global optimal solutions; ③ optimized spectral amplitude weights have physical fault interpretability in the frequency domain, which can locate informative frequency bands and reveal fault feature frequencies to support the rationality of generalized health indices for degradation assessment; ④ generalized health indices based on spectral amplitude weighting can simultaneously achieve the triple goals of machine condition monitoring, fault diagnosis, and degradation assessment, which is conducive to efficient implementation of intelligent machine operation and maintenance. Finally, some future research directions of generalized health indices based on spectral amplitude fusion are fully explored.
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    The World Manufacturing Has Entered a New Era, China Has Created a New Realm of Manufacturing
    LU Yongxiang
    Journal of Mechanical Engineering    2024, 60 (21): 1-3.   DOI: 10.3901/JME.2024.21.001
    Abstract330)      PDF(pc) (163KB)(378)       Save
    The world manufacturing has entered a new era, and the global manufacturing landscape is showing a new pattern. While the United States maintains a global lead in high-tech and advanced military equipment manufacturing, ordinary manufacturing is gradually becoming less substantial and showing a trend of decline year by year. Since the reform and opening up, Chinas manufacturing has shown unique advantages and rapid development, with expectations to surpass the United States by 2035. This article analyzes the characteristics and competitive advantages of Chinas manufacturing. The 20th National Congress of the Communist Party of China has set the great goal of achieving a modernized China as a powerful manufacturing nation in the middle of 21th century. Chinas manufacturing will make great contributions to the wisdom, green, low-carbon, and sustainable development of China and human society!
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    Design and Experimental Study of Whole-body Obstacle Avoidance Strategy for Snake Robots
    LI Peng, WANG Liuyin, WANG Gang, MA Shugen
    Journal of Mechanical Engineering    2024, 60 (21): 4-13.   DOI: 10.3901/JME.2024.21.004
    Abstract321)      PDF(pc) (553KB)(243)       Save
    To solve the problems of low obstacle avoidance efficiency and collision of some joints with obstacles in micro snake robots, a new whole-body obstacle avoidance strategy for snake robots is proposed based on model predictive control. A guidance strategy is also proposed that is applicable to the unique structure of snake robots. The proposed obstacle avoidance strategy can both accurately follow the target path when there is no obstacle and efficiently avoid obstacles when there is an obstacle and quickly return to the original path. Different from the existing strategies that can only guarantee that the head or center of mass of the snake robot does not collide with obstacles, our proposed strategy can guarantee that all joints do not collide with obstacles, and the efficiency of obstacle avoidance is improved without considering the maximum collision volume or assuming that the snake’s tail moves strictly according to the trajectory of the snake’s head. In addition, by analyzing the effect of the changing drive structure of the snake robot on the turning efficiency under the fixed gait, a guidance strategy applicable to this type of robot with changing turning efficiency is proposed to avoid the oscillation phenomenon of the robot repeatedly shuttling through the desired path. The effectiveness of the proposed strategies is verified by extensive simulations and experiments.
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    Research Status and Development Trend of Electro-hydrostatic Actuators for Robots
    ZHANG Junhui, NI Xiaohao, ZONG Huaizhi, GUO Yitao, YANG Meisheng, ZHU Qixin, XU Bing
    Journal of Mechanical Engineering    2025, 61 (4): 273-289.   DOI: 10.3901/JME.2025.04.273
    Abstract320)      PDF(pc) (836KB)(412)       Save
    Hydraulic actuated robots are widely used in many scenarios due to their advantages of high payload and strong anti-interference ability. The actuators serve as the muscle of the robot to output force directly, which are significant for the performance of the robot. Among kinds of actuators, electro-hydrostatic actuators(EHA) have the advantages of high integration, high energy efficiency, and high-power density, and have been widely used in robotics, aerospace, engineering equipment, and other fields. The development status of EHA for robots is reviewed from five aspects: robot application, system configuration, hardware composition, control algorithm and development trend of EHA. Firstly, the applications of EHA in articulated robots, wearable robots, legged robots and other fields are introduced, and the system configurations are introduced in terms of fast response and energy. Then, the hardware compositions of EHA are discussed, including motors, hydraulic pumps, actuators and integrated valve blocks and other core components. In addition, this study summarizes the control algorithm of EHA for the control requirements of the hydraulic robots. Finally, the future trends of EHA for robots from the perspectives of components, drive, control and energy saving are presented.
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    Stability Analysis of Two-stage Relief Valve with Balanced Piston Pilot Valve
    YIN Yaobao, WANG Dong, LI Wending, FU Junyong, ZHANG Xinbin, JIAN Hongchao
    Journal of Mechanical Engineering    2025, 61 (6): 299-307.   DOI: 10.3901/JME.2025.06.299
    Abstract315)      PDF(pc) (1058KB)(216)       Save
    Under extremely small space, the pressure control performance of the hydraulic system can be improved by using a two-stage relief valve with a balanced piston pilot valve. In order to address the absence of a transfer function model for an integrated two-stage relief valve in the aerospace industry, the fundamental equation of a two-stage relief valve with a balanced piston pilot valve is established. The balancing piston separates a chamber in front of the pilot poppet, which is coupled with the pilot poppet to form a mass-spring vibration system with high resonant frequency. Additionally, an annular clearance is formed between the balancing piston and the pilot valve body, which is equivalent to an energy storage element, and its break frequency will decrease with the decrease of the clearance. When the break-frequency of the energy storage element is much lower than the natural frequency of the pilot valve mass-spring vibration system, the stability of the pilot valve will be guaranteed, thus improving the stability of the whole valve. The design requirement for the balanced piston is determined by the correlation between the annular clearance value and the stability of the relief valve. Finally, the correctness of the theoretical analysis is verified by experiments.
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    D-ETV:Digital Experiment, Testing and Verification
    TAO Fei, GAO Pengfei, ZHANG Chenyuan, YI Hang, ZOU Xiaofu, WANG Yanlong, ZHANG Jiankang, ZHANG He, LIU Weiran, WANG Kaixuan, YANG Chunxia
    Journal of Mechanical Engineering    2024, 60 (15): 227-254.   DOI: 10.3901/JME.2024.15.227
    Abstract315)      PDF(pc) (3714KB)(235)       Save
    Experiment, testing and verification (ETV) is a general method to understand the fundamental properties and performance of physical objects. ETV results are capable of providing significant reference for decision-making in various stages of the physical objects’ lifecycle. The five phases for the development of ETV is summarized firstly according to the characteristics of typical products and systems, including physical ETV, physical-digital ETV, digital-physical ETV, digital-physical fusion ETV, and digital ETV(D-ETV). Then, the challenges for future development of D-ETV are analyzed, based on the requirements of D-ETV such as accuracy, efficiency, full-coverage, low costs and security. The concept of D-ETV is further explored, the architecture, maturity model, common application process, technology architecture and application system framework of D-ETV are also proposed. Finally, the ten application prospects are introduced according to the proposed architecture and technologies, including digital flight testing, digital wind tunnel experiment, aircraft engine digital testing, digital battlefield decision verification, high-end CNC machine tool digital verification, satellite manufacturing digital verification, digital space station performance testing, recyclable rocket digital verification, nuclear power plant safety digital testing, underwater equipment performance digital verification. The work of this study is expected to provide inspiration and reference for the development of D-ETV, and better meet the requirements on ETV of physical objects during the whole lifecycle.
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    Review on Negative Expansion Materials in Composite Materials and Brazing
    GU Lei, WANG Pengcheng, YAN Yaotian, CHEN Haiyan, LI Wenya
    Journal of Mechanical Engineering    2024, 60 (22): 1-20.   DOI: 10.3901/JME.2024.22.001
    Abstract306)      PDF(pc) (1307KB)(259)       Save
    Negative thermal expansion(NTE) materials show unique advantages in regulating the coefficient of thermal expansion of materials due to their heat-shrinking and cold-expanding nature, which show great potential in the field of composite materials and brazing. The NTE materials are used to regulate the high coefficient of thermal expansion of metal composite filler,which have been widely used in aerospace,biomedicine,sensors,and electronic information. In the field of composite materials,the combination of NTE and positive thermal expansion material can effectively regulate the coefficient of thermal expansion of composite materials,controlling it at a very low or near-zero level. Some researchers have utilized the property of NTE materials to reduce the coefficient of thermal expansion of metal matrix composites,and reduce the failure problem caused by temperature difference. In the field of brazing,due to the large difference in the coefficient of thermal expansion of dissimilar materials,the large residual stresses will be produced in the brazed joints,which seriously affects the performance of the components. The coefficient of thermal expansion of metal composite filler by introducing negative expansion materials,reducing the difference of the coefficient of thermal expansion between the base material and brazing seam. Therefore,the NTE materials effectively reduces the residual stresses of the brazed joints,and achieves the purpose of improving the mechanical properties of the brazed joints.
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    Online Detection and Self-healing Regulation Method of Marine Diesel Engine Shafting Misalignment
    ZHANG Jinjie, WANG Huailei, DOU Quanli, WANG Zijia, MAO Zhiwei
    Journal of Mechanical Engineering    2024, 60 (20): 24-34.   DOI: 10.3901/JME.2024.20.024
    Abstract304)      PDF(pc) (748KB)(177)       Save
    The force of a marine diesel and its shafting are complex. With effects between structure assembly and hull deformation, shaft misalignment often occurs, which can lead to serious accidents such as bearing wear, coupling fracture, and crankshaft fracture. Due to the influence of structural and operational conditions, traditional vibration time-frequency analysis methods struggle to accurately detect and quantify shafting misalignment. Additionally, the characteristic of power and double frequency is easy to be aliased with other fault features and causes misjudgment. Therefore, a model for misalignment morphological characteristics is developed based on the structural features of misaligned shafting. An online detection scheme is proposed to account for misalignment patterns and mechanical structure effects. The research focuses on the diesel output shaft, and a six-degree-of-freedom fault simulation test bench is established for experimental verification of the misalignment detection method. Furthermore, a self-healing control scheme for shafting misalignment faults is proposed and validated through experiments, enabling online self-healing control of such faults. The data demonstrates that the misalignment detection method based on shafting morphological characteristics can achieve online detection of misalignment under different working conditions, with an accuracy rate exceeding 90%. The self-healing control device driven by servo electric cylinder can reduce the misalignment of shafting by more than 75% within 10 s.
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    Digital Shop Floor Manufacturing Capability Modeling and Adaptive Scheduling in Human-cyber-physical Interconnected Environment
    HU Bingtao, ZHONG Ruirui, FENG Yixiong, YANG Chen, WANG Tianyue, HONG Zhaoxi, TAN Jianrong
    Journal of Mechanical Engineering    2025, 61 (3): 23-39.   DOI: 10.3901/JME.2025.03.023
    Abstract302)      PDF(pc) (819KB)(283)       Save
    The development of Industry 5.0 presents higher requirements for the informatization, digitization, and intelligence of the manufacturing industry. To address the important challenges of the lack of traditional workshop manufacturing capacity organizational paradigm and intelligent scheduling technology, a digital workshop manufacturing capacity modeling and adaptive scheduling technology in the human-cyber-physical interconnected environment is proposed to achieve high-fidelity modeling of complex workshop manufacturing capacity and efficient scheduling of production resources. In order to effectively manage the production elements in the digital workshop, a digital workshop manufacturing capacity modeling technology that integrates the human-cyber-physical system is proposed. In addition, a deep reinforcement learning-driven adaptive scheduling algorithm (DRL-AS) is devised for the digital workshop, which models the flexible job shop scheduling problem in the form of heterogeneous directed acyclic graphs. Considering the complex coupling relationship between operations and machines, a multi-factor representation method based on hierarchical self-attention mechanism is designed to extract global features of the environmental state and assist the agent in making high-quality decisions. Proximal policy optimization (PPO) algorithm is used to train the proposed adaptive scheduling technology. Experimental results show that the scheduling performance and generalization performance of the proposed method are significantly better than those of the comparison algorithms.
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    Review: Application Status and Key Technologies of Wire-driven Flexible Manipulator in Power Industry
    DIAN Songyi, MA Congjun, XIANG Guofei
    Journal of Mechanical Engineering    2025, 61 (9): 211-230.   DOI: 10.3901/JME.2025.09.211
    Abstract301)      PDF(pc) (1907KB)(153)       Save
    As a working tool of power robot, wire-driven flexible manipulator plays an important role in the field of key equipment operation and maintenance in the power industry. The application status of wire-driven flexible manipulators in power transformation and power generation mainly in nuclear power is summarized. The key technologies of wire-driven flexible manipulators applied in power scenarios are reviewed, and the research status and existing problems in structure design, modelling control, sensing detection, motion planning and human-machine interaction technology of wire-driven flexible manipulators are analyzed. Finally, the wire-driven flexible manipulator development trend of the operation and maintenance of key equipment in the power industry and other industrial fields is prospected.
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    Design and Experimental Study of High Water-based Cam Lobe Hydraulic Motor with Low Speed, High Torque and Flow Distribution Valve
    ZHAO Jiyun, MAN Jiaxiang, YU Mingquan, HAN Jing, WANG Yunfei, CAO Chao
    Journal of Mechanical Engineering    2025, 61 (4): 365-379.   DOI: 10.3901/JME.2025.04.365
    Abstract297)      PDF(pc) (1258KB)(215)       Save
    Aiming at the problem of low volumetric efficiency, serious wear and leakage, and low service life in low-speed, high torque water hydraulic motor, a new type of cam lobe high water-based hydraulic motor with flow distribution valve is proposed, which the flow distribution valve and piston rotate synchronously. To analyze reasonable kinematics characteristics of motor piston, the profile parameters of inner curve cam and flow distribution cam are studied and designed. The water lubrication characteristics of the piston-roller pair are analyzed, and the lubrication state of piston-roller pair is boundary lubrication. A piston-roller pair with Peek (poly ether-ether-ketone) coatings is designed to reduce the contact stress, and its performance is verified by experiments. A flow distribution valve that meets the requirements of high water-based media is studied and designed. The working characteristics of the flow distribution valve under different pressures and opening frequencies are tested, and key technical parameters are determined for the reliable flow distribution design in high water-based motor. Meanwhile, a simulation model of the valve flow distribution high water-based motor is established in AMESim software, and the instantaneous output characteristics of motor are analyzed. Finally, the prototype of high water-based hydraulic motor with flow distribution valve is developed and the test system of prototype is built. The experimental results indicate that the flow distribution valve can work stably under pressure of 21 MPa and rotating speed of 15 r/min. The maximum working pressure, output torque and rotating speed range of prototype are 21 MPa, 3 264 N·m and 1-10 r/min respectively. The maximum volumetric efficiency reaches 99.6%.
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    Static Modeling and Analysis of Cable-driven Continuum Robots under Large Load
    LEI Fei, LIU Siyu, LIAO Junbei, GUO Zhao, WANG Zhirui, YAN Tong, DANG Ruina, SU Bo
    Journal of Mechanical Engineering    2024, 60 (15): 28-37.   DOI: 10.3901/JME.2024.15.028
    Abstract292)      PDF(pc) (894KB)(237)       Save
    Currently, continuum robots have weak load capacity and cannot meet the application requirements of large loads. Therefore, a cable-driven continuum robot based on distributed elastic elements that can withstand large loads is designed. The robot has passive compliance and can be utilized for applications such as cushioning, energy saving condition. In order to build the static model between the bending deformation of the continuum robot and the external load, Newton-Euler equations under external loads are established, and numerical solvers are designed for simulation. Compared with the classical constant curvature model, the simulation results are more consistent with the actual deformation. Three groups of experiments are conducted for horizontal, vertical, and circular motions at the end of the continuum robot. The results show that under a 7.5 kg load, the maximum average error between the edge points of the robot disks and corresponding simulation points is 6.58 mm, and the mean square error is 4.50 mm. These values respectively account for 2.87% and 1.96% of the total length of the continuum robot, indicating that the robot can achieve accurate motion under large loads and verifying its feasibility in large loads.
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    Human-robot Autonomous Collaboration Method of Smart Manufacturing Systems Based on Large Language Model and Machine Vision
    HUANG Sihan, CHEN Jianpeng, XU Zhe, YAN Yan, WANG Guoxin
    Journal of Mechanical Engineering    2025, 61 (3): 130-141.   DOI: 10.3901/JME.2025.03.130
    Abstract290)      PDF(pc) (954KB)(267)       Save
    In Industry 4.0, the emerging technologies such as artificial intelligence, big data, and the Internet of Things are appearing endlessly, accelerating the transformation and upgrading of the manufacturing industry. In this process, industry robot plays an increasingly important role, which also lays a solid foundation for the high-quality development of intelligent/smart manufacturing. With the proposal of Industry 5.0, human centricity concept becomes popular, which has given birth to the emerging field of human-centric smart manufacturing. The boundary between human and robot in the smart manufacturing systems gets blurred, and the research on human-robot autonomous collaboration has attracted more and more attentions. Therefore, proposes a human-robot autonomous collaboration method based on large language model and machine vision to improve the intelligence level of human-robot collaboration. First, dynamic perception of the working process for human-robot collaboration is carried out by the fusion of machine vision and deep learning, where the fusion of YOLO and transfer learning is adopted to accurately identify the operate progress and the long short-term memory network and attention mechanism are combined to recognize the actions of operator. Second, the large language model is fine-tuned for human-robot collaboration to realize autonomous operating decision for smart robot during the dynamic work process. Finally, a reducer assembly case is used to verify the effectiveness of the proposed method.
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    Development Status and Prospect of Marine Intelligent Equipment and System
    MA Yong, HU Zushuo, WANG Wenqi, CHANG Xingshan, YAN Xinping
    Journal of Mechanical Engineering    2024, 60 (20): 181-192.   DOI: 10.3901/JME.2024.20.181
    Abstract281)      PDF(pc) (579KB)(320)       Save
    Marine intelligent equipment and systems include the various intelligent devices installed on the ship, as well as the overall system that connects and works together among these devices to strengthen the efficiency and safety of the ship. These systems encompass intelligent navigation, energy efficiency, engine room management, maintenance, integrated platform management, and shore-based maritime systems. They focus not only on the intelligence of individual devices but also on the synergy and optimization of the entire system. Currently, significant progress has been achieved in the research and application of such devices both home and aboard, yet challenges remain in technology, coordination, and environmental protection. Moving forward, as information technology and the Internet of Things continue to evolve, marine intelligent devices and systems are expected to become more widespread and their research more profound, especially in automation and remote control technologies. These advancements are anticipated to make significant contributions to the safety and environmental sustainability of the maritime industry.
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    Lightweight Surface Defect Detection Method of Steel
    WANG Qi, YE Renchuan, MA Guojie, MA Peijue, FAN Jie, YANG Wenlong
    Journal of Mechanical Engineering    2025, 61 (8): 18-31.   DOI: 10.3901/JME.2025.08.018
    Abstract280)      PDF(pc) (977KB)(273)       Save
    Aiming at the problems of low detection efficiency, poor detection accuracy and poor real-time performance of traditional steel surface defect detection methods, An algorithm for surface defect identification of lightweight steel based on improved YOLOv5 is proposed, which is suitable for the engineering deployment of hardware equipment with low cost, low computational power and low memory. Firstly, K-means++ algorithm is used to cluster anchor boxes in the NEU-DET dataset to optimize the matching degree between the prior box and the ground-truth box. Then, by improving the activation function and loss function, HardSwish activation function reduces the computational cost and improves the stability at the same time, while SIoU loss function can effectively accelerate the convergence speed of the network. Secondly, in order to extract rich details of the target region, the CA coordinate attention module is added on the basis of the original YOLOv5 algorithm. Furthermore, the improved Repvgg block is introduced by referring to the structure reparameterization, and the number of model channels is halved to further increase the engineering deployability of the model. Finally, through ablation experiment and a series of comparative experiments, the performance of the proposed algorithm is proved to be superior. Compared with the original YOLOv5 algorithm, the number of parameters is reduced by about 73.6%, the floating point calculation is reduced by about 72.3%, and the mAP value is increased by 1.5%. The results provide a new method and idea for the fine inspection of steel surface defects and have practical significance for improving the quality of steel products.
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    Probabilistic Fatigue Research of Mechanical Structures: State-of-the-Art and Future Trends
    LIAO Ding, ZHU Shunpeng, NIU Xiaopeng, HE Jinchao, WANG Qingyuan
    Journal of Mechanical Engineering    2025, 61 (8): 47-74.   DOI: 10.3901/JME.2025.08.047
    Abstract280)      PDF(pc) (821KB)(313)       Save
    Fatigue failure is one of the most encountered problems with cyclically loaded mechanical structures. Affected by multi-source uncertainties arising from material property, load spectrum, geometrical dimension, etc., fatigue damage evolution generally shows certain variability which cannot be ignored. In particular, the computation is sometimes very sensitive to tiny input changes, in which varying quantities over reasonable ranges can even lead to outputs with 1 000 times difference. Under this circumstance, traditional design criteria which combine deterministic models and safety/scatter factors no longer work, and methods developed from the probabilistic perspective with reasonable and accurate descriptions of uncertain inputs are highly expected to meet the requirements, including the determination of the redundancy and inspection periods, as well as the establishment of maintenance schedules, and retirement policies, in response to the tendency of reliability-based optimal design in modern structural engineering. To boost the development of probabilistic fatigue modelling and emphasize its crucial significance in fatigue reliability design, this paper systematically recalls research backgrounds, fatigue scatter sources, fatigue behaviour variability, basic elements in fatigue reliability and developing trends, and ends with conclusions.
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