Cell mechanics is essential to cell development and function,and its dynamics evolution reflects the physiological state of cells.Here,we investigate the dynamical mechanical properties of single cells under various d...Cell mechanics is essential to cell development and function,and its dynamics evolution reflects the physiological state of cells.Here,we investigate the dynamical mechanical properties of single cells under various drug conditions,and present two mathematical approaches to quantitatively characterizing the cell physiological state.It is demonstrated that the cellular mechanical properties upon the drug action increase over time and tend to saturate,and can be mathematically characterized by a linear timeinvariant dynamical model.It is shown that the transition matrices of dynamical cell systems significantly improve the classification accuracies of the cells under different drug actions.Furthermore,it is revealed that there exists a positive linear correlation between the cytoskeleton density and the cellular mechanical properties,and the physiological state of a cell in terms of its cytoskeleton density can be predicted from its mechanical properties by a linear regression model.This study builds a relationship between the cellular mechanical properties and the cellular physiological state,adding information for evaluating drug efficacy.展开更多
High-precision and real-time diagnosis of sucker rod pumping system(SRPS)is important for quickly mastering oil well operations.Deep learning-based method for classifying the dynamometer card(DC)of oil wells is an eff...High-precision and real-time diagnosis of sucker rod pumping system(SRPS)is important for quickly mastering oil well operations.Deep learning-based method for classifying the dynamometer card(DC)of oil wells is an efficient diagnosis method.However,the input of the DC as a two-dimensional image into the deep learning framework suffers from low feature utilization and high computational effort.Additionally,different SRPSs in an oil field have various system parameters,and the same SRPS generates different DCs at different moments.Thus,there is heterogeneity in field data,which can dramatically impair the diagnostic accuracy.To solve the above problems,a working condition recognition method based on 4-segment time-frequency signature matrix(4S-TFSM)and deep learning is presented in this paper.First,the 4-segment time-frequency signature(4S-TFS)method that can reduce the computing power requirements is proposed for feature extraction of DC data.Subsequently,the 4S-TFSM is constructed by relative normalization and matrix calculation to synthesize the features of multiple data and solve the problem of data heterogeneity.Finally,a convolutional neural network(CNN),one of the deep learning frameworks,is used to determine the functioning conditions based on the 4S-TFSM.Experiments on field data verify that the proposed diagnostic method based on 4S-TFSM and CNN(4S-TFSM-CNN)can significantly improve the accuracy of working condition recognition with lower computational cost.To the best of our knowledge,this is the first work to discuss the effect of data heterogeneity on the working condition recognition performance of SRPS.展开更多
Rapid online analysis of liquid slag is essential for optimizing the quality and energy efficiency of steel production. To investigate the key factors that affect the online measurement of refined slag using laser-ind...Rapid online analysis of liquid slag is essential for optimizing the quality and energy efficiency of steel production. To investigate the key factors that affect the online measurement of refined slag using laser-induced breakdown spectroscopy(LIBS), this study examined the effects of slag composition and temperature on the intensity and stability of the LIBS spectra. The experimental temperature was controlled at three levels: 1350℃, 1400℃, and 1450℃. The results showed that slag composition and temperature significantly affected the intensity and stability of the LIBS spectra. Increasing the Fe content and temperature in the slag reduces its viscosity, resulting in an enhanced intensity and stability of the LIBS spectra. Additionally, 42 refined slag samples were quantitatively analyzed for Fe, Si, Ca, Mg, Al, and Mn at 1350℃, 1400℃, and 1450℃.The normalized full spectrum combined with partial least squares(PLS) quantification modeling was used, using the Ca Ⅱ 317.91 nm spectral line as an internal standard. The results show that using the internal standard normalization method can significantly reduce the influence of spectral fluctuations. Meanwhile, a temperature of 1450℃ has been found to yield superior results compared to both 1350℃ and 1400℃, and it is advantageous to conduct a quantitative analysis of the slag when it is in a “water-like” state with low viscosity.展开更多
This paper proposes a unified trajectory optimization approach that simultaneously optimizes the trajectory of the center of mass and footholds for legged locomotion.Based on a generic point-mass model,the approach is...This paper proposes a unified trajectory optimization approach that simultaneously optimizes the trajectory of the center of mass and footholds for legged locomotion.Based on a generic point-mass model,the approach is formulated as a nonlinear optimization problem,incorporating constraints such as robot kinematics,dynamics,ground reaction forces,obstacles,and target location.The unified optimization approach can be applied to both long-term motion planning and the reactive online planning through the use of model predictive control,and it incorporates vector field guidance to converge to the long-term planned motion.The effectiveness of the approach is demonstrated through simulations and physical experiments,showing its ability to generate a variety of walking and jumping gaits,as well as transitions between them,and to perform reactive walking in obstructed environments.展开更多
To understand the anisotropy dependence of the damage evolution and material removal during the machining process of MgF_(2) single crystals,nanoscratch tests of MgF_(2) single crystals with different crystal planes a...To understand the anisotropy dependence of the damage evolution and material removal during the machining process of MgF_(2) single crystals,nanoscratch tests of MgF_(2) single crystals with different crystal planes and directions were systematically performed,and surface morphologies of the scratched grooves under different conditions were analyzed.The experimental results indicated that anisotropy considerably affected the damage evolution in the machining process of MgF_(2) single crystals.A stress field model induced by the scratch was developed by considering the anisotropy,which indicated that during the loading process,median cracks induced by the tensile stress initiated and propagated at the front of the indenter.Lateral cracks induced by tensile stress initiated and propagated on the subsurface during the unloading process.In addition,surface radial cracks induced by the tensile stress were easily generated during the unloading process.The stress change led to the deflection of the propagation direction of lateral cracks.Therefore,the lateral cracks propagated to the workpiece surface,resulting in brittle removal in the form of chunk chips.The plastic deformation parameter indicated that the more the slip systems were activated,the more easily the plastic deformation occurred.The cleavage fracture parameter indicated that the cracks propagated along the activated cleavage planes,and the brittle chunk removal was owing to the subsurface cleavage cracks propagating to the crystal surface.Under the same processing parameters,the scratch of the(001)crystal plane along the[100]crystal-orientation was found to be the most conducive to achieving plastic machining of MgF_(2) single crystals.The theoretical results agreed well with the experimental results,which will not only enhance the understanding of the anisotropy dependence of the damage evolution and removal process during the machining of MgF_(2) crystals,but also provide a theoretical foundation for achieving the high-efficiency and low-damage processing of anisotropic single crystals.展开更多
Multifunctional structures(MFSs)integrate diverse functions to achieve superior properties.However,conventional design and manufacturing methods—which generally lack quality control and largely depend on complex equi...Multifunctional structures(MFSs)integrate diverse functions to achieve superior properties.However,conventional design and manufacturing methods—which generally lack quality control and largely depend on complex equipment with multiple stations to achieve the integration of distinct materials and devices—are unable to satisfy the requirements of MFS applications in emerging industries such as aerospace engineering.Motivated by the concept of design for manufacturing,we adopt a layer regulation method with an established optimization model to design typical MFSs with load-bearing,electric,heat-conduction,and radiation-shielding functions.A high-temperature in situ additive manufacturing(AM)technology is developed to print various metallic wires or carbon fiber-reinforced high-meltingpoint polyetheretherketone(PEEK)composites.It is found that the MFS,despite its low mass,exceeds the stiffness of the PEEK substrate by 21.5%.The embedded electrics remain functional after the elastic deformation stage.Compared with those of the PEEK substrate,the equivalent thermal conductivity of the MFS beneath the central heat source area is enhanced by 568.0%,and the radiation shielding is improved by 27.9%.Moreover,a satellite prototype with diverse MFSs is rapidly constructed as an illustration.This work provides a systematic approach for high-performance design and advanced manufacturing,which exhibits considerable prospects for both the function expansion and performance enhancement of industrial equipment.展开更多
The development of projection-based stereolithography additive manufacturing techniques and magnetic photosensitive resins has provided a powerful approach to fabricate miniaturized magnetic functional devices with co...The development of projection-based stereolithography additive manufacturing techniques and magnetic photosensitive resins has provided a powerful approach to fabricate miniaturized magnetic functional devices with complex three-dimensional spatial structures.However,the present magnetic photosensitive resins face great challenges in the trade-off between high ferromagnetism and excellent printing quality.To address these challenges,we develop a novel NdFeB-Fe_(3)O_(4) magnetic photosensitive resin comprising 20 wt.%solid loading of magnetic particles,which can be used to fabricate high-precision and ferromagnetic functional devices via micro-continuous liquid interface production process.This resin combining ferromagnetic NdFeB microparticles and strongly absorbing Fe_(3)O_(4) nanoparticles is able to provide ferromagnetic capabilities and excellent printing quality simultaneously compared to both existing soft and hard magnetic photosensitive resins.The established penetration depth model reveals the effect of particle size,solid loading,and absorbance on the curing characteristics of magnetic photosensitive resin.A high-precision forming and ferromagnetic capability of the NdFeB-Fe_(3)O_(4) magnetic photosensitive resin are comprehensively demonstrated.It is found that the photosensitive resin(NdFeB:Fe_(3)O_(4)=1:1)can print samples with sub-40μm fine features,reduced by 87%compared to existing hard magnetic photosensitive resin,and exhibits significantly enhanced coercivity and remanence in comparison with existing soft magnetic photosensitive resins,showing by an increase of 24 times and 6 times,respectively.The reported NdFeB-Fe_(3)O_(4) magnetic photosensitive resin is anticipated to provide a new functional material for the design and manufacture of next-generation micro-robotics,electromagnetic sensor,and magneto-thermal devices.展开更多
Birds in nature exhibit excellent long-distance flight capabilities through formation flight,which could reduce energy consumption and improve flight efficiency.Inspired by the biological habits of birds,this paper pr...Birds in nature exhibit excellent long-distance flight capabilities through formation flight,which could reduce energy consumption and improve flight efficiency.Inspired by the biological habits of birds,this paper proposes an autonomous formation flight control method for Large-sized Flapping-Wing Flying Robots(LFWFRs),which can enhance their search range and flight efficiency.First,the kinematics model for LFWFRs is established.Then,an autonomous flight controller based on this model is designed,which has multiple flight control modes,including attitude stabilization,course keeping,hovering,and so on.Second,a formation flight control method is proposed based on the leader–follower strategy and periodic characteristics of flapping-wing flight.The up and down fluctuation of the fuselage of each LFWFR during wing flapping is considered in the control algorithm to keep the relative distance,which overcomes the trajectory divergence caused by sensor delay and fuselage fluctuation.Third,typical formation flight modes are realized,including straight formation,circular formation,and switching formation.Finally,the outdoor formation flight experiment is carried out,and the proposed autonomous formation flight control method is verified in real environment.展开更多
Large-scale solar sails can provide power to spacecraft for deep space exploration.A new type of telescopic tubular mast(TTM)driven by a bistable carbon fiber-reinforced polymer tube was designed in this study to solv...Large-scale solar sails can provide power to spacecraft for deep space exploration.A new type of telescopic tubular mast(TTM)driven by a bistable carbon fiber-reinforced polymer tube was designed in this study to solve the problem of contact between the sail membrane and the spacecraft under light pressure.Compared with the traditional TTM,it has a small size,light weight,high extension ratio,and simple structure.The anti-blossoming and self-unlocking structure of the proposed TTM was described.We aimed to simplify the TTM with a complex structure into a beam model with equal linear mass density,and the simulation results showed good consistency.The dynamic equation was derived based on the equivalent model,and the effects of different factors on the vibration characteristics of the TTM were analyzed.The performance parameters were optimized based on a multiobjective genetic algorithm,and prototype production and load experiments were conducted.The results show that the advantages of the new TTM can complete the deployment of large-scale solar sails,which is valuable for future deep space exploration.展开更多
In recent years,designing a soft robot that can jump continuously and quickly explore in a narrow space has been a hot research topic.With the continuous efforts of researchers,many types of actuators have been develo...In recent years,designing a soft robot that can jump continuously and quickly explore in a narrow space has been a hot research topic.With the continuous efforts of researchers,many types of actuators have been developed and successfully employed to actuate the rapid locomotion of soft robots.Although these mechanisms have enabled soft robots with excellent movement capabilities,they largely rely on external energy supply cables,which greatly limits their applications.Therefore,it is still a big challenge to realize the unconstrained movement of the soft robot and the flexible adjustment of the movement direction in a narrow space.Here,a wireless magnetically controlled soft jumping robot with single-leg is proposed,which can achieve continuous and rapid jumping motion.What's more interesting is that by changing the frequency and waveform of the control signal,this soft robot can easily switch between forward and backward motions.This motion direction switching function enables the magnetically controlled soft robot to return to the initial position without adjusting the direction when it completes the operation in a narrow pipe or takes the wrong path,which greatly improves the motion efficiency of the soft jumping robot and broadens its application field.展开更多
The electrically driven large-load-ratio six-legged robot with engineering capability can be widely used in outdoor and planetary exploration.However,due to the particularity of its parallel structure,the effective ut...The electrically driven large-load-ratio six-legged robot with engineering capability can be widely used in outdoor and planetary exploration.However,due to the particularity of its parallel structure,the effective utilization rate of energy is not high,which has become an important obstacle to its practical application.To research the power consumption characteristics of robot mobile system is beneficial to speed up it toward practicability.Based on the configuration and walking modes of robot,the mathematical model of the power consumption of mobile system is set up.In view of the tripod gait is often selected for the six-legged robots,the simplified power consumption model of mobile system under the tripod gait is established by means of reducing the dimension of the robot’s statically indeterminate problem and constructing the equal force distribution.Then,the power consumption of robot mobile system is solved under different working conditions.The variable tendencies of the power consumption of robot mobile system are respectively obtained with changes in the rotational angles of hip joint and knee joint,body height,and span.The articulated rotational zones and the ranges of body height and span are determined under the lowest power consumption.According to the walking experiments of prototype,the variable tendencies of the average power consumption of robot mobile system are respectively acquired with changes in duty ratio,body height,and span.Then,the feasibility and correctness of theory analysis are verified in the power consumption of robot mobile system.The proposed analysis method in this paper can provide a reference on the lower power research of the large-load-ratio multi-legged robots.展开更多
The accurate and intelligent identification of the working conditions of a sucker-rod pumping system is necessary. As onshore oil extraction gradually enters its mid-to late-stage, the cost required to train a deep le...The accurate and intelligent identification of the working conditions of a sucker-rod pumping system is necessary. As onshore oil extraction gradually enters its mid-to late-stage, the cost required to train a deep learning working condition recognition model for pumping wells by obtaining enough new working condition samples is expensive. For the few-shot problem and large calculation issues of new working conditions of oil wells, a working condition recognition method for pumping unit wells based on a 4-dimensional time-frequency signature (4D-TFS) and meta-learning convolutional shrinkage neural network (ML-CSNN) is proposed. First, the measured pumping unit well workup data are converted into 4D-TFS data, and the initial feature extraction task is performed while compressing the data. Subsequently, a convolutional shrinkage neural network (CSNN) with a specific structure that can ablate low-frequency features is designed to extract working conditions features. Finally, a meta-learning fine-tuning framework for learning the network parameters that are susceptible to task changes is merged into the CSNN to solve the few-shot issue. The results of the experiments demonstrate that the trained ML-CSNN has good recognition accuracy and generalization ability for few-shot working condition recognition. More specifically, in the case of lower computational complexity, only few-shot samples are needed to fine-tune the network parameters, and the model can be quickly adapted to new classes of well conditions.展开更多
Traditional rigid-body in-pipe robots usually have complex and heavy structures with limited flexibility and adaptability.Although soft in-pipe robots have great improvements in flexibility,they still have manufacturi...Traditional rigid-body in-pipe robots usually have complex and heavy structures with limited flexibility and adaptability.Although soft in-pipe robots have great improvements in flexibility,they still have manufacturing difficulties due to their reliance on high-performance soft materials.Tensegrity structure is a kind of self-stressed spatial structure consisting discrete rigid struts connected by a continuous net of tensional flexible strings,which combines the advantages of both rigid structures and soft structures.By applying tensegrity structures into robotics,this paper proposes a novel worm-like tensegrity robot for moving inside pipes.First,a robot module capable of body deformation is designed based on the concept of tensegrity and its deformation performance is analyzed.Then,the optimal parameters of the module are obtained based on the tensegrity form-finding.The deformation ability of the tensegrity module is tested experimentally.Finally,the worm-like tensegrity robot that can crawl inside pipes is developed by connecting three modules in series.Motion performance and load capacity are tested on the prototype of the worm-like tensegrity robot by experiments of moving in horizontal pipe,vertical pipe,and elbow pipe.Experimental results demonstrate the effectiveness of the proposed design and suggest that the robot has high compliance,mobility,and adaptability although with simple structure and low cost.展开更多
With the growing demand for miniaturized workspaces,the demand for microrobots has been increasing in robotics research.Compared to traditional rigid robots,soft robots have better robustness and safety.With a flexibl...With the growing demand for miniaturized workspaces,the demand for microrobots has been increasing in robotics research.Compared to traditional rigid robots,soft robots have better robustness and safety.With a flexible structure,soft robots can undergo large deformations and achieve a variety of motion states.Researchers are working to design and fabricate flexible robots based on biomimetic principles,using magnetic fields for cable-free actuation.In this study,we propose an inchworm-shaped soft robot driven by a magnetic field.First,a robot is designed and fabricated and force analysis is performed.Then,factors affecting the soft robot’s motion speed are examined,including the spacing between the magnets and the strength and frequency of the magnetic field.On this basis,the motion characteristics of the robot in different shapes are explored,and its motion modes such as climbing are experimentally investigated.The results show that the motion of the robot can be controlled in a two-dimensional plane,and its movement speed can be controlled by adjusting the strength of the magnetic field and other factors.Our proposed soft robot is expected to find extensive applications in various fields.展开更多
The inherent compliance of continuum robots holds great promise in the fields of soft manipulation and safe human–robot interaction.This compliance reduces the risk of damage to the manipulated object and its surroun...The inherent compliance of continuum robots holds great promise in the fields of soft manipulation and safe human–robot interaction.This compliance reduces the risk of damage to the manipulated object and its surroundings.However,continuum robots possess theoretically infinite degrees of freedom,and this high flexibility usually leads to complex deformations when subjected to external forces and positional constraints.Describing these complex deformations is the main challenge in modeling continuum robots.In this study,we investigated a novel variable curvature modeling method for continuum robots,considering external forces and positional constraints.The robot configuration curve is described using the developed mechanical model,and then the robot is fitted to the curve.A ten-section continuum robot prototype with a length of 1 m was developed in order to validate the model.The feasibility and accuracy of the model were verified by the ability of the robot to reach target points and track complex trajectories with a load.This work was able to serve as a new perspective for the design analysis and motion control of continuum robots.展开更多
Rehabilitation using exoskeleton robots can effectively remediate dysfunction and restore post-stroke survivors’ physical ability. However, low kinematic compatibility and poor self-participation of post-stroke patie...Rehabilitation using exoskeleton robots can effectively remediate dysfunction and restore post-stroke survivors’ physical ability. However, low kinematic compatibility and poor self-participation of post-stroke patients in rehabilitation restrict the outcomes of exoskeleton-based therapy. The study presents an Unpowered Shoulder Complex Exoskeleton (USCE), consisting of Shoulder Girdle Mechanism (SGM), Ball-and-Socket Joint Mechanism (BSM), Gravity Compensating Mechanism (GCM) and Adjustable Alignment Design (AAD), to achieve self-rehabilitation of shoulder via energy transfer from the healthy upper limb to the affected counterpart of post-stroke hemiplegic patients. The SGM and AAD are designed to improve the kinematic compatibility by compensating for displacements of the glenohumeral joint with the adaptable size of USCE for different wearers. The BSM and GCM can transfer the body movement and energy from the healthy half of the body to the affected side without external energy input and enhance the self-participation with sick posture correction. The experimental results show that the USCE can provide high kinematic compatibility with 90.9% movement similarity between human and exoskeleton. Meanwhile, the motion ability of a post-stroke patient’s affected limb can be increased through energy transfer. It is expected that USCE can improve outcomes of home-based self-rehabilitation.展开更多
Artificial intelligence is currently achieving impressive success in all fields.However,autonomous navigation remains a major challenge for AI.Reinforcement learning is used for target navigation to simulate the inter...Artificial intelligence is currently achieving impressive success in all fields.However,autonomous navigation remains a major challenge for AI.Reinforcement learning is used for target navigation to simulate the interaction between the brain and the environment at the behavioral level,but the Artificial Neural Network trained by reinforcement learning cannot match the autonomous mobility of humans and animals.The hippocampus–striatum circuits are considered as key circuits for target navigation planning and decision-making.This paper aims to construct a bionic navigation model of reinforcement learning corresponding to the nervous system to improve the autonomous navigation performance of the robot.The ventral striatum is considered to be the behavioral evaluation region,and the hippocampal–striatum circuit constitutes the position–reward association.In this paper,a set of episode cognition and reinforcement learning system simulating the mechanism of hippocampus and ventral striatum is constructed,which is used to provide target guidance for the robot to perform autonomous tasks.Compared with traditional methods,this system reflects the high efficiency of learning and better Environmental Adaptability.Our research is an exploration of the intersection and fusion of artificial intelligence and neuroscience,which is conducive to the development of artificial intelligence and the understanding of the nervous system.展开更多
We propose a novel image segmentation algorithm to tackle the challenge of limited recognition and segmentation performance in identifying welding seam images during robotic intelligent operations.Initially,to enhance...We propose a novel image segmentation algorithm to tackle the challenge of limited recognition and segmentation performance in identifying welding seam images during robotic intelligent operations.Initially,to enhance the capability of deep neural networks in extracting geometric attributes from depth images,we developed a novel deep geometric convolution operator(DGConv).DGConv is utilized to construct a deep local geometric feature extraction module,facilitating a more comprehensive exploration of the intrinsic geometric information within depth images.Secondly,we integrate the newly proposed deep geometric feature module with the Fully Convolutional Network(FCN8)to establish a high-performance deep neural network algorithm tailored for depth image segmentation.Concurrently,we enhance the FCN8 detection head by separating the segmentation and classification processes.This enhancement significantly boosts the network’s overall detection capability.Thirdly,for a comprehensive assessment of our proposed algorithm and its applicability in real-world industrial settings,we curated a line-scan image dataset featuring weld seams.This dataset,named the Standardized Linear Depth Profile(SLDP)dataset,was collected from actual industrial sites where autonomous robots are in operation.Ultimately,we conducted experiments utilizing the SLDP dataset,achieving an average accuracy of 92.7%.Our proposed approach exhibited a remarkable performance improvement over the prior method on the identical dataset.Moreover,we have successfully deployed the proposed algorithm in genuine industrial environments,fulfilling the prerequisites of unmanned robot operations.展开更多
Many attentions for structural synthesis are paid to planar linkages and parallel mechanisms, while design novel pyramid deployable truss structure(PDTS) of satellite SAR mainly depends on experience of designer. To d...Many attentions for structural synthesis are paid to planar linkages and parallel mechanisms, while design novel pyramid deployable truss structure(PDTS) of satellite SAR mainly depends on experience of designer. To design novel configuration of PDTS, a two-step topology structure synthesis and analysis approach is proposed. Firstly, a conceptual configuration of PDTS is synthesized. Weighted graph and weighted adjacency matrix are established to realize topological description for PDTS. Graph properties are then summarized to distinguish differentia between PDTS and other type structures. According to graph properties, a procedure for synthesis conceptual configuration of PDTS is presented. Secondly, join relationship of components in a PDTS is analyzed. Kinematic chain and corresponding incidence/adjacency matrix are employed to analyze join relationship of PDTS. Properties and simplified rules of kinematic chain are extracted to construct kinematic chain. A procedure for construction kinematic chain of PDTS is then established. Finally, with this two-step approach all 11 rectangular pyramid deployable structures whose folded state is planar are discovered and their kinematic chains are constructed. Based on synthesis results, a novel deployable support structure for satellite SAR is designed. The proposed research can be applied to obtain some novel PDTSs, which is of great importance to design some novel deployable support structures for satellite SAR antenna.展开更多
Underwater gliders,which glide through water columns by use of a pair of wings,are efficient long-distance,long-duration marine environment observatory platforms.The Sea-Wing underwater glider,developed by the Shenyan...Underwater gliders,which glide through water columns by use of a pair of wings,are efficient long-distance,long-duration marine environment observatory platforms.The Sea-Wing underwater glider,developed by the Shenyang Institute of Automation,CAS,is designed for the application of deep-sea environment variables observation.The system components,the mechanical design,and the control system design of the Sea-Wing underwater glider are described in this paper.The pitch and roll adjusting models are derived based on the mechanical design,and the adjusting capabilities for the pitch and roll are analyzed according to the models.Field experiments have been carried out for validating the gliding motion and the ability of measuring ocean environment variables.Experimental results of the motion performances of the glider are presented.展开更多
基金This work was supported by the National Natural Science Foundation of China(Grant Nos:U1908215,61925307,62003338,and 61933008)CAS Project for Young Scientists in Basic Research(Grant No:YSBR-041)+2 种基金Liaoning Revitalization Talents Program(Grant No:XLYC2002014)Natural Science Foundation of Liaoning Province of China(Grant No:2020-ZLLH-47)Joint fund of Science&Technology Department of Liaoning Province and State Key Laboratory of Robotics,China(Grant No:2019-KF-01-01).
文摘Cell mechanics is essential to cell development and function,and its dynamics evolution reflects the physiological state of cells.Here,we investigate the dynamical mechanical properties of single cells under various drug conditions,and present two mathematical approaches to quantitatively characterizing the cell physiological state.It is demonstrated that the cellular mechanical properties upon the drug action increase over time and tend to saturate,and can be mathematically characterized by a linear timeinvariant dynamical model.It is shown that the transition matrices of dynamical cell systems significantly improve the classification accuracies of the cells under different drug actions.Furthermore,it is revealed that there exists a positive linear correlation between the cytoskeleton density and the cellular mechanical properties,and the physiological state of a cell in terms of its cytoskeleton density can be predicted from its mechanical properties by a linear regression model.This study builds a relationship between the cellular mechanical properties and the cellular physiological state,adding information for evaluating drug efficacy.
基金We would like to thank the associate editor and the reviewers for their constructive comments.This work was supported in part by the National Natural Science Foundation of China under Grant 62203234in part by the State Key Laboratory of Robotics of China under Grant 2023-Z03+1 种基金in part by the Natural Science Foundation of Liaoning Province under Grant 2023-BS-025in part by the Research Program of Liaoning Liaohe Laboratory under Grant LLL23ZZ-02-02.
文摘High-precision and real-time diagnosis of sucker rod pumping system(SRPS)is important for quickly mastering oil well operations.Deep learning-based method for classifying the dynamometer card(DC)of oil wells is an efficient diagnosis method.However,the input of the DC as a two-dimensional image into the deep learning framework suffers from low feature utilization and high computational effort.Additionally,different SRPSs in an oil field have various system parameters,and the same SRPS generates different DCs at different moments.Thus,there is heterogeneity in field data,which can dramatically impair the diagnostic accuracy.To solve the above problems,a working condition recognition method based on 4-segment time-frequency signature matrix(4S-TFSM)and deep learning is presented in this paper.First,the 4-segment time-frequency signature(4S-TFS)method that can reduce the computing power requirements is proposed for feature extraction of DC data.Subsequently,the 4S-TFSM is constructed by relative normalization and matrix calculation to synthesize the features of multiple data and solve the problem of data heterogeneity.Finally,a convolutional neural network(CNN),one of the deep learning frameworks,is used to determine the functioning conditions based on the 4S-TFSM.Experiments on field data verify that the proposed diagnostic method based on 4S-TFSM and CNN(4S-TFSM-CNN)can significantly improve the accuracy of working condition recognition with lower computational cost.To the best of our knowledge,this is the first work to discuss the effect of data heterogeneity on the working condition recognition performance of SRPS.
基金financially supported by the National Key R&D Program Projects of China (No.2021YFB3202402)National Natural Science Foundation of China (No.62173321)。
文摘Rapid online analysis of liquid slag is essential for optimizing the quality and energy efficiency of steel production. To investigate the key factors that affect the online measurement of refined slag using laser-induced breakdown spectroscopy(LIBS), this study examined the effects of slag composition and temperature on the intensity and stability of the LIBS spectra. The experimental temperature was controlled at three levels: 1350℃, 1400℃, and 1450℃. The results showed that slag composition and temperature significantly affected the intensity and stability of the LIBS spectra. Increasing the Fe content and temperature in the slag reduces its viscosity, resulting in an enhanced intensity and stability of the LIBS spectra. Additionally, 42 refined slag samples were quantitatively analyzed for Fe, Si, Ca, Mg, Al, and Mn at 1350℃, 1400℃, and 1450℃.The normalized full spectrum combined with partial least squares(PLS) quantification modeling was used, using the Ca Ⅱ 317.91 nm spectral line as an internal standard. The results show that using the internal standard normalization method can significantly reduce the influence of spectral fluctuations. Meanwhile, a temperature of 1450℃ has been found to yield superior results compared to both 1350℃ and 1400℃, and it is advantageous to conduct a quantitative analysis of the slag when it is in a “water-like” state with low viscosity.
基金supported by the Natural Science Foundation of Hebei Province of China(no.E2022203095)Cultivation Project for Basic Research and Innovation of Yanshan University(no.2021LGQN004)National Natural Science Foundation of China(no.51905465 and No.52122503).
文摘This paper proposes a unified trajectory optimization approach that simultaneously optimizes the trajectory of the center of mass and footholds for legged locomotion.Based on a generic point-mass model,the approach is formulated as a nonlinear optimization problem,incorporating constraints such as robot kinematics,dynamics,ground reaction forces,obstacles,and target location.The unified optimization approach can be applied to both long-term motion planning and the reactive online planning through the use of model predictive control,and it incorporates vector field guidance to converge to the long-term planned motion.The effectiveness of the approach is demonstrated through simulations and physical experiments,showing its ability to generate a variety of walking and jumping gaits,as well as transitions between them,and to perform reactive walking in obstructed environments.
基金supported by the National Natural Science Foundation of China (52005134&51975154)China Postdoctoral Science Foundation (2022T150163, 2020M670901)+4 种基金Self-Planned Task (No. SKLRS202214B) of State Key Laboratory of Robotics and System (HIT)Heilongjiang Postdoctoral Fund (LBH-Z20016)Shenzhen Science and Technology Program (GJHZ20210705142804012)Fundamental Research Funds for the Central Universities(FRFCU5710051122)Open Fund of ZJUT Xinchang Research Institute
文摘To understand the anisotropy dependence of the damage evolution and material removal during the machining process of MgF_(2) single crystals,nanoscratch tests of MgF_(2) single crystals with different crystal planes and directions were systematically performed,and surface morphologies of the scratched grooves under different conditions were analyzed.The experimental results indicated that anisotropy considerably affected the damage evolution in the machining process of MgF_(2) single crystals.A stress field model induced by the scratch was developed by considering the anisotropy,which indicated that during the loading process,median cracks induced by the tensile stress initiated and propagated at the front of the indenter.Lateral cracks induced by tensile stress initiated and propagated on the subsurface during the unloading process.In addition,surface radial cracks induced by the tensile stress were easily generated during the unloading process.The stress change led to the deflection of the propagation direction of lateral cracks.Therefore,the lateral cracks propagated to the workpiece surface,resulting in brittle removal in the form of chunk chips.The plastic deformation parameter indicated that the more the slip systems were activated,the more easily the plastic deformation occurred.The cleavage fracture parameter indicated that the cracks propagated along the activated cleavage planes,and the brittle chunk removal was owing to the subsurface cleavage cracks propagating to the crystal surface.Under the same processing parameters,the scratch of the(001)crystal plane along the[100]crystal-orientation was found to be the most conducive to achieving plastic machining of MgF_(2) single crystals.The theoretical results agreed well with the experimental results,which will not only enhance the understanding of the anisotropy dependence of the damage evolution and removal process during the machining of MgF_(2) crystals,but also provide a theoretical foundation for achieving the high-efficiency and low-damage processing of anisotropic single crystals.
基金supported by the National Natural Science Foundation of China(51822503,U20A20297,and 51975142)Key-Area Research and Development Program of Guangdong Province,China(2020B090923003)。
文摘Multifunctional structures(MFSs)integrate diverse functions to achieve superior properties.However,conventional design and manufacturing methods—which generally lack quality control and largely depend on complex equipment with multiple stations to achieve the integration of distinct materials and devices—are unable to satisfy the requirements of MFS applications in emerging industries such as aerospace engineering.Motivated by the concept of design for manufacturing,we adopt a layer regulation method with an established optimization model to design typical MFSs with load-bearing,electric,heat-conduction,and radiation-shielding functions.A high-temperature in situ additive manufacturing(AM)technology is developed to print various metallic wires or carbon fiber-reinforced high-meltingpoint polyetheretherketone(PEEK)composites.It is found that the MFS,despite its low mass,exceeds the stiffness of the PEEK substrate by 21.5%.The embedded electrics remain functional after the elastic deformation stage.Compared with those of the PEEK substrate,the equivalent thermal conductivity of the MFS beneath the central heat source area is enhanced by 568.0%,and the radiation shielding is improved by 27.9%.Moreover,a satellite prototype with diverse MFSs is rapidly constructed as an illustration.This work provides a systematic approach for high-performance design and advanced manufacturing,which exhibits considerable prospects for both the function expansion and performance enhancement of industrial equipment.
基金supported by the National Key Research and Development Program of China(Grant Number2022YFB460001602)National Natural Science Foundation of China(Grant Numbers 52125505,U20A20297)the Key-area Research and Development Program of Guangdong Province(Grant Number 2020B090923003)。
文摘The development of projection-based stereolithography additive manufacturing techniques and magnetic photosensitive resins has provided a powerful approach to fabricate miniaturized magnetic functional devices with complex three-dimensional spatial structures.However,the present magnetic photosensitive resins face great challenges in the trade-off between high ferromagnetism and excellent printing quality.To address these challenges,we develop a novel NdFeB-Fe_(3)O_(4) magnetic photosensitive resin comprising 20 wt.%solid loading of magnetic particles,which can be used to fabricate high-precision and ferromagnetic functional devices via micro-continuous liquid interface production process.This resin combining ferromagnetic NdFeB microparticles and strongly absorbing Fe_(3)O_(4) nanoparticles is able to provide ferromagnetic capabilities and excellent printing quality simultaneously compared to both existing soft and hard magnetic photosensitive resins.The established penetration depth model reveals the effect of particle size,solid loading,and absorbance on the curing characteristics of magnetic photosensitive resin.A high-precision forming and ferromagnetic capability of the NdFeB-Fe_(3)O_(4) magnetic photosensitive resin are comprehensively demonstrated.It is found that the photosensitive resin(NdFeB:Fe_(3)O_(4)=1:1)can print samples with sub-40μm fine features,reduced by 87%compared to existing hard magnetic photosensitive resin,and exhibits significantly enhanced coercivity and remanence in comparison with existing soft magnetic photosensitive resins,showing by an increase of 24 times and 6 times,respectively.The reported NdFeB-Fe_(3)O_(4) magnetic photosensitive resin is anticipated to provide a new functional material for the design and manufacture of next-generation micro-robotics,electromagnetic sensor,and magneto-thermal devices.
基金This work was supported in part by the National Natural Science Foundation of China(Grant No.62233001)Shenzhen excellent scientific and technological innovation talent training project(Grant No.RCJC20200714114436040)the Basic Research Program of Shenzhen(Grant No.JCYJ20190806142816524).
文摘Birds in nature exhibit excellent long-distance flight capabilities through formation flight,which could reduce energy consumption and improve flight efficiency.Inspired by the biological habits of birds,this paper proposes an autonomous formation flight control method for Large-sized Flapping-Wing Flying Robots(LFWFRs),which can enhance their search range and flight efficiency.First,the kinematics model for LFWFRs is established.Then,an autonomous flight controller based on this model is designed,which has multiple flight control modes,including attitude stabilization,course keeping,hovering,and so on.Second,a formation flight control method is proposed based on the leader–follower strategy and periodic characteristics of flapping-wing flight.The up and down fluctuation of the fuselage of each LFWFR during wing flapping is considered in the control algorithm to keep the relative distance,which overcomes the trajectory divergence caused by sensor delay and fuselage fluctuation.Third,typical formation flight modes are realized,including straight formation,circular formation,and switching formation.Finally,the outdoor formation flight experiment is carried out,and the proposed autonomous formation flight control method is verified in real environment.
基金Supported by National Key R&D Program of China (Grant No.2018YFB1304600)National Natural Science Foundation of China (Grant No.51905527)+1 种基金CAS Interdisciplinary Innovation Team of China (Grant No.JCTD-2018-11)State Key Laboratory of Robotics Foundation of China (Grant No.Y91Z0303)。
文摘Large-scale solar sails can provide power to spacecraft for deep space exploration.A new type of telescopic tubular mast(TTM)driven by a bistable carbon fiber-reinforced polymer tube was designed in this study to solve the problem of contact between the sail membrane and the spacecraft under light pressure.Compared with the traditional TTM,it has a small size,light weight,high extension ratio,and simple structure.The anti-blossoming and self-unlocking structure of the proposed TTM was described.We aimed to simplify the TTM with a complex structure into a beam model with equal linear mass density,and the simulation results showed good consistency.The dynamic equation was derived based on the equivalent model,and the effects of different factors on the vibration characteristics of the TTM were analyzed.The performance parameters were optimized based on a multiobjective genetic algorithm,and prototype production and load experiments were conducted.The results show that the advantages of the new TTM can complete the deployment of large-scale solar sails,which is valuable for future deep space exploration.
基金support from the National Natural Science Foundation of China (No.61803088)Joint fund of the Science&Technology Department of Liaoning Province and the State Key Laboratory of Robotics,China (Grant No.2021-KF-22-13)Natural Science Foundation of Fujian Province,China (No.2022J01543).
文摘In recent years,designing a soft robot that can jump continuously and quickly explore in a narrow space has been a hot research topic.With the continuous efforts of researchers,many types of actuators have been developed and successfully employed to actuate the rapid locomotion of soft robots.Although these mechanisms have enabled soft robots with excellent movement capabilities,they largely rely on external energy supply cables,which greatly limits their applications.Therefore,it is still a big challenge to realize the unconstrained movement of the soft robot and the flexible adjustment of the movement direction in a narrow space.Here,a wireless magnetically controlled soft jumping robot with single-leg is proposed,which can achieve continuous and rapid jumping motion.What's more interesting is that by changing the frequency and waveform of the control signal,this soft robot can easily switch between forward and backward motions.This motion direction switching function enables the magnetically controlled soft robot to return to the initial position without adjusting the direction when it completes the operation in a narrow pipe or takes the wrong path,which greatly improves the motion efficiency of the soft jumping robot and broadens its application field.
基金National Natural Science Foundation of China(Grant No.51505335)Industry University Cooperation Collaborative Education Project of the Department of Higher Education of the Ministry of Education of China(Grant No.202102517001)Doctor Startup Projects of TUTE of China(Grant No.KYQD1806)。
文摘The electrically driven large-load-ratio six-legged robot with engineering capability can be widely used in outdoor and planetary exploration.However,due to the particularity of its parallel structure,the effective utilization rate of energy is not high,which has become an important obstacle to its practical application.To research the power consumption characteristics of robot mobile system is beneficial to speed up it toward practicability.Based on the configuration and walking modes of robot,the mathematical model of the power consumption of mobile system is set up.In view of the tripod gait is often selected for the six-legged robots,the simplified power consumption model of mobile system under the tripod gait is established by means of reducing the dimension of the robot’s statically indeterminate problem and constructing the equal force distribution.Then,the power consumption of robot mobile system is solved under different working conditions.The variable tendencies of the power consumption of robot mobile system are respectively obtained with changes in the rotational angles of hip joint and knee joint,body height,and span.The articulated rotational zones and the ranges of body height and span are determined under the lowest power consumption.According to the walking experiments of prototype,the variable tendencies of the average power consumption of robot mobile system are respectively acquired with changes in duty ratio,body height,and span.Then,the feasibility and correctness of theory analysis are verified in the power consumption of robot mobile system.The proposed analysis method in this paper can provide a reference on the lower power research of the large-load-ratio multi-legged robots.
基金supported in part by the National Natural Science Foundation of China under Grant U1908212,62203432 and 92067205in part by the State Key Laboratory of Robotics of China under Grant 2023-Z03 and 2023-Z15in part by the Natural Science Foundation of Liaoning Province under Grant 2020-KF-11-02.
文摘The accurate and intelligent identification of the working conditions of a sucker-rod pumping system is necessary. As onshore oil extraction gradually enters its mid-to late-stage, the cost required to train a deep learning working condition recognition model for pumping wells by obtaining enough new working condition samples is expensive. For the few-shot problem and large calculation issues of new working conditions of oil wells, a working condition recognition method for pumping unit wells based on a 4-dimensional time-frequency signature (4D-TFS) and meta-learning convolutional shrinkage neural network (ML-CSNN) is proposed. First, the measured pumping unit well workup data are converted into 4D-TFS data, and the initial feature extraction task is performed while compressing the data. Subsequently, a convolutional shrinkage neural network (CSNN) with a specific structure that can ablate low-frequency features is designed to extract working conditions features. Finally, a meta-learning fine-tuning framework for learning the network parameters that are susceptible to task changes is merged into the CSNN to solve the few-shot issue. The results of the experiments demonstrate that the trained ML-CSNN has good recognition accuracy and generalization ability for few-shot working condition recognition. More specifically, in the case of lower computational complexity, only few-shot samples are needed to fine-tune the network parameters, and the model can be quickly adapted to new classes of well conditions.
基金National Natural Science Foundation of China,52005293,Yixiang Liu,U20A20201Yixiang Liu,Shandong Provincial Natural Science Foundation,ZR2020QE152+3 种基金Yixiang Liu,Key R&D Program of Hebei Province,China,20311803DYixiang Liu,Key R&D Program of Shandong Province,China,2021CXGC011304Yixiang Liu,Research Project of the State Key Laboratory of Mechanical Transmissions,Chongqing University,SKLMT-MSKFKT-202118Yixiang Liu,Fundamental Research Funds of Shandong University,2021JCG001,Yixiang Liu.
文摘Traditional rigid-body in-pipe robots usually have complex and heavy structures with limited flexibility and adaptability.Although soft in-pipe robots have great improvements in flexibility,they still have manufacturing difficulties due to their reliance on high-performance soft materials.Tensegrity structure is a kind of self-stressed spatial structure consisting discrete rigid struts connected by a continuous net of tensional flexible strings,which combines the advantages of both rigid structures and soft structures.By applying tensegrity structures into robotics,this paper proposes a novel worm-like tensegrity robot for moving inside pipes.First,a robot module capable of body deformation is designed based on the concept of tensegrity and its deformation performance is analyzed.Then,the optimal parameters of the module are obtained based on the tensegrity form-finding.The deformation ability of the tensegrity module is tested experimentally.Finally,the worm-like tensegrity robot that can crawl inside pipes is developed by connecting three modules in series.Motion performance and load capacity are tested on the prototype of the worm-like tensegrity robot by experiments of moving in horizontal pipe,vertical pipe,and elbow pipe.Experimental results demonstrate the effectiveness of the proposed design and suggest that the robot has high compliance,mobility,and adaptability although with simple structure and low cost.
基金the funding provided by the National Natural Science Foundation of China(Project no.62273289)Graduate Innovation Foundation of Yantai University and Joint fund of Science&Technology Department of Liaoning Province and State Key Laboratory of Robotics(Project no.2021-KF-22-03).
文摘With the growing demand for miniaturized workspaces,the demand for microrobots has been increasing in robotics research.Compared to traditional rigid robots,soft robots have better robustness and safety.With a flexible structure,soft robots can undergo large deformations and achieve a variety of motion states.Researchers are working to design and fabricate flexible robots based on biomimetic principles,using magnetic fields for cable-free actuation.In this study,we propose an inchworm-shaped soft robot driven by a magnetic field.First,a robot is designed and fabricated and force analysis is performed.Then,factors affecting the soft robot’s motion speed are examined,including the spacing between the magnets and the strength and frequency of the magnetic field.On this basis,the motion characteristics of the robot in different shapes are explored,and its motion modes such as climbing are experimentally investigated.The results show that the motion of the robot can be controlled in a two-dimensional plane,and its movement speed can be controlled by adjusting the strength of the magnetic field and other factors.Our proposed soft robot is expected to find extensive applications in various fields.
基金Supported by National Natural Science Foundation of China(Grant Nos.51975566,61821005,U1908214)Key Research Program of Frontier Sciences,CAS,China(Grant No.ZDBS-LY-JSC011).
文摘The inherent compliance of continuum robots holds great promise in the fields of soft manipulation and safe human–robot interaction.This compliance reduces the risk of damage to the manipulated object and its surroundings.However,continuum robots possess theoretically infinite degrees of freedom,and this high flexibility usually leads to complex deformations when subjected to external forces and positional constraints.Describing these complex deformations is the main challenge in modeling continuum robots.In this study,we investigated a novel variable curvature modeling method for continuum robots,considering external forces and positional constraints.The robot configuration curve is described using the developed mechanical model,and then the robot is fitted to the curve.A ten-section continuum robot prototype with a length of 1 m was developed in order to validate the model.The feasibility and accuracy of the model were verified by the ability of the robot to reach target points and track complex trajectories with a load.This work was able to serve as a new perspective for the design analysis and motion control of continuum robots.
基金supported by the National Key R&D Program of China(Grant No.2016YFE0206200)the National Natural Science Foundation of China(Grant Nos.U1908215,91848201,61821005 and 61973316)Liaoning Revitalizaiton Talents Program(Grant No.XLYC2002014).
文摘Rehabilitation using exoskeleton robots can effectively remediate dysfunction and restore post-stroke survivors’ physical ability. However, low kinematic compatibility and poor self-participation of post-stroke patients in rehabilitation restrict the outcomes of exoskeleton-based therapy. The study presents an Unpowered Shoulder Complex Exoskeleton (USCE), consisting of Shoulder Girdle Mechanism (SGM), Ball-and-Socket Joint Mechanism (BSM), Gravity Compensating Mechanism (GCM) and Adjustable Alignment Design (AAD), to achieve self-rehabilitation of shoulder via energy transfer from the healthy upper limb to the affected counterpart of post-stroke hemiplegic patients. The SGM and AAD are designed to improve the kinematic compatibility by compensating for displacements of the glenohumeral joint with the adaptable size of USCE for different wearers. The BSM and GCM can transfer the body movement and energy from the healthy half of the body to the affected side without external energy input and enhance the self-participation with sick posture correction. The experimental results show that the USCE can provide high kinematic compatibility with 90.9% movement similarity between human and exoskeleton. Meanwhile, the motion ability of a post-stroke patient’s affected limb can be increased through energy transfer. It is expected that USCE can improve outcomes of home-based self-rehabilitation.
基金funded by National Key R&D Program of China to Fusheng Zha with Grant numbers 2020YFB13134Natural Science Foundation of China to Fusheng Zha with Grant numbers U2013602,52075115,51521003,61911530250.
文摘Artificial intelligence is currently achieving impressive success in all fields.However,autonomous navigation remains a major challenge for AI.Reinforcement learning is used for target navigation to simulate the interaction between the brain and the environment at the behavioral level,but the Artificial Neural Network trained by reinforcement learning cannot match the autonomous mobility of humans and animals.The hippocampus–striatum circuits are considered as key circuits for target navigation planning and decision-making.This paper aims to construct a bionic navigation model of reinforcement learning corresponding to the nervous system to improve the autonomous navigation performance of the robot.The ventral striatum is considered to be the behavioral evaluation region,and the hippocampal–striatum circuit constitutes the position–reward association.In this paper,a set of episode cognition and reinforcement learning system simulating the mechanism of hippocampus and ventral striatum is constructed,which is used to provide target guidance for the robot to perform autonomous tasks.Compared with traditional methods,this system reflects the high efficiency of learning and better Environmental Adaptability.Our research is an exploration of the intersection and fusion of artificial intelligence and neuroscience,which is conducive to the development of artificial intelligence and the understanding of the nervous system.
基金This work was supported by the National Natural Science Foundation of China(Grant No.U20A20197).
文摘We propose a novel image segmentation algorithm to tackle the challenge of limited recognition and segmentation performance in identifying welding seam images during robotic intelligent operations.Initially,to enhance the capability of deep neural networks in extracting geometric attributes from depth images,we developed a novel deep geometric convolution operator(DGConv).DGConv is utilized to construct a deep local geometric feature extraction module,facilitating a more comprehensive exploration of the intrinsic geometric information within depth images.Secondly,we integrate the newly proposed deep geometric feature module with the Fully Convolutional Network(FCN8)to establish a high-performance deep neural network algorithm tailored for depth image segmentation.Concurrently,we enhance the FCN8 detection head by separating the segmentation and classification processes.This enhancement significantly boosts the network’s overall detection capability.Thirdly,for a comprehensive assessment of our proposed algorithm and its applicability in real-world industrial settings,we curated a line-scan image dataset featuring weld seams.This dataset,named the Standardized Linear Depth Profile(SLDP)dataset,was collected from actual industrial sites where autonomous robots are in operation.Ultimately,we conducted experiments utilizing the SLDP dataset,achieving an average accuracy of 92.7%.Our proposed approach exhibited a remarkable performance improvement over the prior method on the identical dataset.Moreover,we have successfully deployed the proposed algorithm in genuine industrial environments,fulfilling the prerequisites of unmanned robot operations.
基金Supported by the College Discipline Innovation Wisdom Plan in China(Grant No.B07018)National Natural Science Foundation of China(Grant Nos.50935002,11002039)
文摘Many attentions for structural synthesis are paid to planar linkages and parallel mechanisms, while design novel pyramid deployable truss structure(PDTS) of satellite SAR mainly depends on experience of designer. To design novel configuration of PDTS, a two-step topology structure synthesis and analysis approach is proposed. Firstly, a conceptual configuration of PDTS is synthesized. Weighted graph and weighted adjacency matrix are established to realize topological description for PDTS. Graph properties are then summarized to distinguish differentia between PDTS and other type structures. According to graph properties, a procedure for synthesis conceptual configuration of PDTS is presented. Secondly, join relationship of components in a PDTS is analyzed. Kinematic chain and corresponding incidence/adjacency matrix are employed to analyze join relationship of PDTS. Properties and simplified rules of kinematic chain are extracted to construct kinematic chain. A procedure for construction kinematic chain of PDTS is then established. Finally, with this two-step approach all 11 rectangular pyramid deployable structures whose folded state is planar are discovered and their kinematic chains are constructed. Based on synthesis results, a novel deployable support structure for satellite SAR is designed. The proposed research can be applied to obtain some novel PDTSs, which is of great importance to design some novel deployable support structures for satellite SAR antenna.
基金supported by the State Key Laboratory of Robotics (Grant No. 2009-Z05)the Knowledge Innovation Program of the Chinese Academy of Sciences (Grant No. KZCX2-YW-JS205)the National High Technology Research and Development Program of China (863 Program,Grant No. 2006AA09Z157)
文摘Underwater gliders,which glide through water columns by use of a pair of wings,are efficient long-distance,long-duration marine environment observatory platforms.The Sea-Wing underwater glider,developed by the Shenyang Institute of Automation,CAS,is designed for the application of deep-sea environment variables observation.The system components,the mechanical design,and the control system design of the Sea-Wing underwater glider are described in this paper.The pitch and roll adjusting models are derived based on the mechanical design,and the adjusting capabilities for the pitch and roll are analyzed according to the models.Field experiments have been carried out for validating the gliding motion and the ability of measuring ocean environment variables.Experimental results of the motion performances of the glider are presented.
