查看更多>>摘要：Grinding,a critical precision machining process for difficult-to-cut alloys,has undergone continual technological advancements to improve machining efficiency.However,the sustainability of this process is gaining heightened attention due to significant challenges associated with the substantial specific grinding energy and the extensive heat generated when working with difficult-to-cut alloys,renowned for their exceptional physical and mechanical properties.In response to these challenges,the widespread application of massive coolant in manufacturing indus-tries to dissipate grinding heat has led to complex post-cleaning and disposal processes.This,in turn,has resulted in issues such as large energy consumption,a considerable carbon footprint,and concerns related to worker health and safety,which have become the main factors that restrict the development of grinding technology.This paper provides a holistic review of sustainability in grinding difficult-to-cut alloys,encompassing current trends and future directions.The examination extends to developing grinding technologies explicitly tailored for these alloys,compre-hensively evaluating their sustainability performance.Additionally,the exploration delves into innovative sustainable technologies,such as heat pipe/oscillating heat pipe grinding wheels,minimum quantity lubrication,cryogenic cool-ing,and others.These groundbreaking technologies aim to reduce dependence on hazardous coolants,minimizing energy and resource consumption and carbon emissions associated with coolant-related or subsequent disposal pro-cesses.The essence of these technologies lies in their potential to revolutionize traditional grinding practices,present-ing environmentally friendly alternatives.Finally,future development trends and research directions are put forward to pursue the current limitation of sustainable grinding for difficult-to-cut alloys.This paper can guide future research and development efforts toward more environmentally friendly grinding operations by understanding the current state of sustainable grinding and identifying emerging trends.
查看更多>>摘要：Machine tools,often referred to as the"mother machines"of the manufacturing industry,are crucial in developing smart manufacturing and are increasingly becoming more intelligent.Digital twin technology can promote machine tool intelligence and has attracted considerable research interest.However,there is a lack of clear and system-atic analyses on how the digital twin technology enables machine tool intelligence.Herein,digital twin modeling was identified as an enabling technology for machine tool intelligence based on a comparative study of the charac-teristics of machine tool intelligence and digital twin.The review then delves into state-of-the-art digital twin mode-ling-enabled machine tool intelligence,examining it from the aspects of data-based modeling and mechanism-data dual-driven modeling.Additionally,it highlights three bottleneck issues facing the field.Considering these problems,the architecture of a digital twin machine tool(DTMT)is proposed,and three key technologies are expounded in detail:Data perception and fusion technology,mechanism-data-knowledge hybrid-driven digital twin modeling and virtual-real synchronization technology,and dynamic optimization and collaborative control technology for mul-tilevel parameters.Finally,future research directions for the DTMT are discussed.This work can provide a foundation basis for the research and implementation of digital-twin modeling-enabled machine tool intelligence,making it significant for developing intelligent machine tools.
查看更多>>摘要：The most widely adopted method for diagnosing respiratory infectious diseases is to conduct polymerase chain reac-tion(PCR)assays on patients'respiratory specimens,which are collected through either nasal or oropharyngeal swabs.The manual swab sampling process poses a high risk to the examiner and may cause false-negative results owing to improper sampling.In this paper,we propose a pneumatically actuated soft end-effector specifically designed to achieve all of the tasks involved in swab sampling.The soft end-effector utilizes circumferential instability to ensure grasping stability,and exhibits several key properties,including high load-to-weight ratio,error tolerance,and variable swab-tip stiffness,leading to successful automatic robotic oropharyngeal swab sampling,from loosening and tight-ening the transport medium tube cap,holding the swab,and conducting sampling,to snapping off the swab tail and sterilizing itself.Using an industrial collaborative robotic arm,we integrated the soft end-effector,force sensor,camera,lights,and remote-control stick,and developed a robotic oropharyngeal swab sampling system.Using this swab sampling system,we conducted oropharyngeal swab-sampling tests on 20 volunteers.Our Digital PCR assay results(RNase P RNA gene absolute copy numbers for the samples)revealed that our system successfully collected sufficient numbers of cells from the pharyngeal wall for respiratory disease diagnosis.In summary,we have developed a pharyngeal swab-sampling system based on an"enveloping"soft actuator,studied the sampling process,and imple-mented whole-process robotic oropharyngeal swab-sampling.
查看更多>>摘要：Existing mobile robots mostly use graph search algorithms for path planning,which suffer from relatively low plan-ning efficiency owing to high redundancy and large computational complexity.Due to the limitations of the neigh-borhood search strategy,the robots could hardly obtain the most optimal global path.A global path planning algorithm,denoted as EDG*,is proposed by expanding nodes using a well-designed expanding disconnected graph operator(EDG)in this paper.Firstly,all obstacles are marked and their corners are located through the map pre-processing.Then,the EDG operator is designed to find points in non-obstruction areas to complete the rapid expansion of disconnected nodes.Finally,the EDG*heuristic iterative algorithm is proposed.It selects the candidate node through a specific valuation function and realizes the node expansion while avoiding collision with a minimum offset.Path planning experiments were conducted in a typical indoor environment and on the public dataset CSM.The result shows that the proposed EDG*reduced the planning time by more than 90％and total length of paths reduced by more than 4.6％.Compared to A*,Dijkstra and J PS,EDG*does not show an exponential explosion effect in map size.The EDG*showed better performance in terms of path smoothness,and collision avoidance.This shows that the EDG*algorithm proposed in this paper can improve the efficiency of path planning and enhance path quality.
查看更多>>摘要：The lower limb exoskeletons are used to assist wearers in various scenarios such as medical and industrial settings.Complex modeling errors of the exoskeleton in different application scenarios pose challenges to the robustness and stability of its control algorithm.The Radial Basis Function(RBF)neural network is used widely to compensate for modeling errors.In order to solve the problem that the current RBF neural network controllers cannot guarantee the asymptotic stability,a neural network robust control algorithm based on computed torque method is proposed in this paper,focusing on trajectory tracking.It innovatively incorporates the robust adaptive term while introduc-ing the RBF neural network term,improving the compensation ability for modeling errors.The stability of the algo-rithm is proved by Lyapunov method,and the effectiveness of the robust adaptive term is verified by the simulation.Experiments wearing the exoskeleton under different walking speeds and scenarios were carried out,and the results show that the absolute value of tracking errors of the hip and knee joints of the exoskeleton are consistently less than 1.5°and 2.5°,respectively.The proposed control algorithm effectively compensates for modeling errors and exhibits high robustness.
查看更多>>摘要：Exoskeletons generally require accurate dynamic models to design the model-based controller conveniently under the human-robot interaction condition.However,due to unknown model parameters such as the mass,moment of inertia and mechanical size,the dynamic model of exoskeletons is difficult to construct.Hence,an enhanced whale optimization algorithm(EWOA)is proposed to identify the exoskeleton model parameters.Meanwhile,the periodic excitation trajectories are designed by finite Fourier series to input the desired position demand of exoskeletons with mechanical physical constraints.Then a backstepping controller based on the identi-fied model is adopted to improve the human-robot wearable comfortable performance under cooperative motion.Finally,the proposed Model parameters identification and control are verified by a two-DOF exoskeletons platform.The knee joint motion achieves a steady-state response after 0.5 s.Meanwhile,the position error of hip joint response is less than 0.03 rad after 0.9 s.In addition,the steady-state human-robot interaction torque of the two joints is con-strained within 15 N.m.This research proposes a whale optimization algorithm to optimize the excitation trajectory and identify model parameters.Furthermore,an enhanced mutation strategy is adopted to avoid whale evolution's unsatisfactory local optimal value.
Yusuf Suleiman DambattaChanghe LiMohd SayutiAhmed A D Sarhan...
115-136页
查看更多>>摘要：Minimum quantity Lubrication(MQL)is a sustainable lubrication system that is famous in many machining systems.It involve the spray of an infinitesimal amount of mist-like lubricants during machining processes.The MQL system is affirmed to exhibit an excellent machining performance,and it is highly economical.The nanofluids are understood to exhibit excellent lubricity and heat evacuation capability,compared to pure oil-based MQL system.Studies have shown that the surface quality and amount of energy expended in the grinding operations can be reduced consid-erably due to the positive effect of these nanofluids.This work presents an experimental study on the tribological performance of SiO2 nanofluid during grinding of Si3N4 ceramic.The effect different grinding modes and lubrication systems during the grinding operation was also analyzed.Different concentrations of the SiO2 nanofluid was manu-factured using canola,corn and sunflower oils.The quantitative evaluation of the grinding process was done based on the amount of grinding forces,specific grinding energy,frictional coefficient,and surface integrity.It was found that the canola oil exhibits optimal lubrication performance compared to corn oil,sunflower oil,and traditional lubrication systems.Additionally,the introduction of ultrasonic vibrations with the SiO2 nanofluid in MQL system was found to reduce the specific grinding energy,normal grinding forces,tangential grinding forces,and surface roughness by 65％,57％,65％,and 18％respectively.Finally,regression analysis was used to obtain an optimum parameter combinations.The observations from this work will aid the smooth transition towards ecofriendly and sus-tainable machining of engineering ceramics.
查看更多>>摘要：Inconel 718(IN718)alloy is widely applied to fabricate high temperature resistant or corrosion resistant parts due to its excellent mechanical performance.However,the machining of IN718 alloy is difficult as it may cause serious tool wear and poor surface quality(SQ)of the workpiece.In this work,grinding experiments on IN718 alloy at different speeds were conducted by using a CBN grinding wheel.The relationship between grinding speed,SQ and subsurface damage(SSD)was well studied.With increasing grinding speed,surface roughness decreased,and SQ was greatly improved.Meanwhile,the microhardness of the grinding surface declined as the grinding speed increased.The SSD depth was almost unchanged when the grinding speed was lower than 15 m/s,then it decreased with higher grind-ing speeds.It was attributed to the mechanical-thermal synergistic effect in the grinding process.The results indi-cated that increasing grinding speed can effectively improve the SQ and reduce the SSD of IN718 alloy.The conclu-sion in the work may also provide insight into processing other hard-to-machining materials.
查看更多>>摘要：Laser tracers are a three-dimensional coordinate measurement system that are widely used in industrial measure-ment.We propose a geometric error identification method based on multi-station synchronization laser tracers to enable the rapid and high-precision measurement of geometric errors for gantry-type computer numerical control(CNC)machine tools.This method also improves on the existing measurement efficiency issues in the single-base station measurement method and multi-base station time-sharing measurement method.We consider a three-axis gantry-type CNC machine tool,and the geometric error mathematical model is derived and established based on the combination of screw theory and a topological analysis of the machine kinematic chain.The four-station laser tracers position and measurement points are realized based on the multi-point positioning principle.A self-calibra-tion algorithm is proposed for the coordinate calibration process of a laser tracer using the Levenberg-Marquardt nonlinear least squares method,and the geometric error is solved using Taylor's first-order linearization iteration.The experimental results show that the geometric error calculated based on this modeling method is comparable to the results from the Etalon laser tracer.For a volume of 800 mm × 1000 mm × 350 mm,the maximum differences of the linear,angular,and spatial position errors were 2.0 μm,2.7 μrad,and 12.0 μm,respectively,which verifies the accuracy of the proposed algorithm.This research proposes a modeling method for the precise measurement of errors in machine tools,and the applied nature of this study also makes it relevant both to researchers and those in the industrial sector.
查看更多>>摘要：Textured surfaces with certain micro/nano structures have been proven to possess some advanced functions,such as reducing friction,improving wear and increasing wettability.Accurate prediction of micro/nano surface textures is of great significance for the design,fabrication and application of functional textured surfaces.In this paper,based on the kinematic analysis of cutter teeth,the discretization of ultrasonic machining process,transformation method of coordinate systems and the cubic spline data interpolation,an integrated theoretical model was established to characterize the distribution and geometric features of micro textures on the surfaces machined by different types of ultrasonic vibration-assisted milling(UVAM).Based on the theoretical model,the effect of key process param-eters(vibration directions,vibration dimensions,cutting parameters and vibration parameters)on tool trajectories and microtextured surface morphology in UVAM is investigated.Besides,the effect of phase difference on the ellipti-cal shape in 2D/3D ultrasonic elliptical vibration-assisted milling(UEVAM)was analyzed.Compared to conventional numerical models,the method of the cubic spline data interpolation is applied to the simulation of microtextured surface morphology in UVAM,which is more suitable for characterizing the morphological features of microtextured surfaces than traditional methods due to the presence of numerous micro textures.The prediction of surface rough-ness indicates that the magnitude of ultrasonic amplitude in z-direction should be strictly limited in 1D rotary UVAM,2D and 3D UEVAM due to the unfavorable effect of axial ultrasonic vibration on the surface quality.This study can provide theoretical guidance for the design and fabrication of microtextured surfaces in UVAM.
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