Human Adaptive Mechatronics(HAM)includes human and computer system in a closed loop.Elderly person with disabilities,normally carry out their daily routines with some assistance to move their limbs.With the short fall...Human Adaptive Mechatronics(HAM)includes human and computer system in a closed loop.Elderly person with disabilities,normally carry out their daily routines with some assistance to move their limbs.With the short fall of human care takers,mechatronics devices are used with the likes of exoskeleton and exosuits to assist them.The rehabilitation and occupational therapy equipments utilize the electromyography(EMG)signals to measure the muscle activity potential.This paper focuses on optimizing the HAM model in prediction of intended motion of upper limb with high accuracy and to increase the response time of the system.Limb characteristics extraction from EMG signal and prediction of optimal controller parameters are modeled.Time and frequency based approach of EMG signal are considered for feature extraction.The models used for estimating motion and muscle parameters from EMG signal for carrying out limb movement predictions are validated.Based on the extracted features,optimal parameters are selected by Modified Lion Optimization(MLO)for controlling the HAM system.Finally,supervised machine learning makes predictions at different points in time for individual sensing using Support Vector Neural Network(SVNN).This model is also evaluated based on optimal parameters of motion estimation and the accuracy level along with different optimization models for various upper limb movements.The proposed model of human adaptive controller predicts the limb movement by 96%accuracy.展开更多
LuGre model has been widely used in friction modeling and compensation.However,the new friction regime,named prestiction regime,cannot be accurately characterized by LuGre model in the latest research.With the extensi...LuGre model has been widely used in friction modeling and compensation.However,the new friction regime,named prestiction regime,cannot be accurately characterized by LuGre model in the latest research.With the extensive experimental observations of friction behaviors in the prestiction,some variables were abstracted to depict the rules in the prestiction regime.Based upon the knowledge of friction modeling,a novel friction model including the presliding regime,the gross sliding regime and the prestiction regime was then presented to overcome the shortcomings of the LuGre model.The reason that LuGre model cannot estimate the prestiction friction was analyzed in theory.Feasibility analysis of the proposed model in modeling the prestiction friction was also addressed.A parameter identification method for the proposed model based on multilevel coordinate search algorithm was presented.The proposed friction compensation strategy was composed of a nonlinear friction observer and a feedforward mechanism.The friction observer was designed to estimate the friction force in the presliding and the gross sliding regimes.And the friction force was estimated based on the model in the prestiction regime.The comparative trajectory tracking experiments were conducted on a simulator of inertially stabilization platforms among three control schemes:the single proportional–derivative(PD)control,the PD with LuGre model-based compensation and the PD with compensator based on the presented model.The experimental results reveal that the control scheme based on the proposed model has the best tracking performance.It reduces the peak-to-peak value(PPV)of tracking error to 0.2 mrad,which is improved almost 50%compared with the PD with LuGre model-based compensation.Compared to the single PD control,it reduces the PPV of error by 66.7%.展开更多
Healthcare mechatronics is a typical multidisciplinary field involving machinery,medicine,computer,and automation,which has been widely applied in respiratory therapy,urology robot,rehabilitation exoskeleton,artificia...Healthcare mechatronics is a typical multidisciplinary field involving machinery,medicine,computer,and automation,which has been widely applied in respiratory therapy,urology robot,rehabilitation exoskeleton,artificial heart,etc.Existing progresses has some defects in modeling,design and implementation of healthcare mechatronics.Therefore,exploring new design theories,key technologies and typical applications is an effective to promote the rapid development of this field.展开更多
The development of low-temperature solid oxide fuel cells(LT-SOFCs)is of significant importance for realizing the widespread application of SOFCs.This has stimulated a substantial materials research effort in developi...The development of low-temperature solid oxide fuel cells(LT-SOFCs)is of significant importance for realizing the widespread application of SOFCs.This has stimulated a substantial materials research effort in developing high oxide-ion conductivity in the electrolyte layer of SOFCs.In this context,for the first time,a dielectric material,CaCu_(3)Ti_(4)O_(12)(CCTO)is designed for LT-SOFCs electrolyte application in this study.Both individual CCTO and its heterostructure materials with a p-type Ni_(0.8)Co_(0.15)Al_(0.05)LiO_(2−δ)(NCAL)semiconductor are evaluated as alternative electrolytes in LT-SOFC at 450–550℃.The single cell with the individual CCTO electrolyte exhibits a power output of approximately 263 mW cm^(-2) and an open-circuit voltage(OCV)of 0.95 V at 550℃,while the cell with the CCTO–NCAL heterostructure electrolyte capably delivers an improved power output of approximately 605 mW cm^(-2) along with a higher OCV over 1.0 V,which indicates the introduction of high hole-conducting NCAL into the CCTO could enhance the cell performance rather than inducing any potential short-circuiting risk.It is found that these promising outcomes are due to the interplay of the dielectric material,its structure,and overall properties that led to improve electrochemical mechanism in CCTO–NCAL.Furthermore,density functional theory calculations provide the detailed information about the electronic and structural properties of the CCTO and NCAL and their heterostructure CCTO–NCAL.Our study thus provides a new approach for developing new advanced electrolytes for LT-SOFCs.展开更多
The active sound absorption technique excels in mitigating low-frequency sound waves,yet it falls short when dealing with medium and high-frequency sound waves.To enhance the sound-absorbing effect of medium and high-...The active sound absorption technique excels in mitigating low-frequency sound waves,yet it falls short when dealing with medium and high-frequency sound waves.To enhance the sound-absorbing effect of medium and high-frequency sound waves,a novel semi-active sound absorption method has been introduced.This method modulates the surface impedance of a loudspeaker positioned behind the sound-absorbing material,thereby altering the sound absorption coefficient.The theoretical sound absorption coefficient is calculated using MATLAB and compared with the experimental one.Results show that the method can effectively modulates the absorption coefficient in response to varying incident sound wave frequencies,ensuring that it remains at its peak value.展开更多
3D printing technology enhances the combustion characteristics of hybrid rocket fuels by enabling complex geometries. However, improvements in regression rates and energy properties of monotonous 3D printed fuels have...3D printing technology enhances the combustion characteristics of hybrid rocket fuels by enabling complex geometries. However, improvements in regression rates and energy properties of monotonous 3D printed fuels have been limited. This study explores the impact of poly(vinylidene fluoride) and polydopamine-coated aluminum particles on the thermal and combustion properties of 3D printed hybrid rocket fuels. Physical self-assembly and anti-solvent methods were employed for constructing composite μAl particles. Characterization using SEM, XRD, XPS, FTIR, and μCT revealed a core-shell structure and homogeneous elemental distribution. Thermal analysis showed that PVDF coatings significantly increased the heat of combustion for aluminum particles, with maximum enhancement observed in μAl@PDA@PVDF(denoted as μAl@PF) at 6.20 k J/g. Subsequently, 3D printed fuels with varying pure and composite μAl particle contents were prepared using 3D printing. Combustion tests indicated higher regression rates for Al@PF/Resin composites compared to pure resin, positively correlating with particle content. The fluorocarbon-alumina reaction during the combustion stage intensified Al particle combustion, reducing residue size. A comprehensive model based on experiments provides insights into the combustion process of PDA and PVDF-coated droplets. This study advances the design of 3D-printed hybrid rocket fuels, offering strategies to improve regression rates and energy release, crucial for enhancing solid fuel performance for hybrid propulsion.展开更多
Metal Additive Manufacturing(MAM) technology has become an important means of rapid prototyping precision manufacturing of special high dynamic heterogeneous complex parts. In response to the micromechanical defects s...Metal Additive Manufacturing(MAM) technology has become an important means of rapid prototyping precision manufacturing of special high dynamic heterogeneous complex parts. In response to the micromechanical defects such as porosity issues, significant deformation, surface cracks, and challenging control of surface morphology encountered during the selective laser melting(SLM) additive manufacturing(AM) process of specialized Micro Electromechanical System(MEMS) components, multiparameter optimization and micro powder melt pool/macro-scale mechanical properties control simulation of specialized components are conducted. The optimal parameters obtained through highprecision preparation and machining of components and static/high dynamic verification are: laser power of 110 W, laser speed of 600 mm/s, laser diameter of 75 μm, and scanning spacing of 50 μm. The density of the subordinate components under this reference can reach 99.15%, the surface hardness can reach 51.9 HRA, the yield strength can reach 550 MPa, the maximum machining error of the components is 4.73%, and the average surface roughness is 0.45 μm. Through dynamic hammering and high dynamic firing verification, SLM components meet the requirements for overload resistance. The results have proven that MEM technology can provide a new means for the processing of MEMS components applied in high dynamic environments. The parameters obtained in the conclusion can provide a design basis for the additive preparation of MEMS components.展开更多
In general,the rapid growth of α-Fe clusters is a challenge in high Fe-content Fe-based amorphous alloys,negatively affecting their physical properties.Herein,we introduce an efficient and rapid post-treatment techni...In general,the rapid growth of α-Fe clusters is a challenge in high Fe-content Fe-based amorphous alloys,negatively affecting their physical properties.Herein,we introduce an efficient and rapid post-treatment technique known as ultrasonic vibration rapid processing(UVRP),which enables the formation of high-density strong magnetic α-Fe clusters,thereby enhancing the soft magnetic properties of Fe_(78)Si(13)B_(9) amorphous alloy ribbon.展开更多
Despite the promising progress in conductive hydrogels made with pure conducting polymer,great challenges remain in the interface adhesion and robustness in longterm monitoring.To address these challenges,Prof.Seung H...Despite the promising progress in conductive hydrogels made with pure conducting polymer,great challenges remain in the interface adhesion and robustness in longterm monitoring.To address these challenges,Prof.Seung Hwan Ko and Taek-Soo Kim’s team introduced a laserinduced phase separation and adhesion method for fabricating conductive hydrogels consisting of pure poly(3,4-ethylenedioxythiophene):polystyrene sulfonate on polymer substrates.The laser-induced phase separation and adhesion treated conducting polymers can be selectively transformed into conductive hydrogels that exhibit wet conductivities of 101.4 S cm^(−1) with a spatial resolution down to 5μm.Moreover,they maintain impedance and charge-storage capacity even after 1 h of sonication.The micropatterned electrode arrays demonstrate their potential in long-term in vivo signal recordings,highlighting their promising role in the field of bioelectronics.展开更多
According to surface morphology,microhardness,X-ray diffraction,and static contact angle experiments,the changes in the surface integrity and corrosion resistance of 6061-T6 aluminum alloy after ultrasonic shot peenin...According to surface morphology,microhardness,X-ray diffraction,and static contact angle experiments,the changes in the surface integrity and corrosion resistance of 6061-T6 aluminum alloy after ultrasonic shot peening(USP)were investigated.Results show that the grain size of the material surface is reduced by 43%,the residual compressive stress has an increasing trend,the roughness and hardness are increased by approximately 211.1%and 35%,respectively.And the static contact angle is increased at first,followed by a slight decrease.Weighing,scanning electron microscope,and energy dispersive spectrometer were used to study the samples after a cyclic corrosion test.Results show that USP reduces the corrosion rate by 41.2%.A model of surface corrosion mechanism of USP is developed,and the mechanism of USP to improve the corrosion resistance of materials is discussed.The introduction of compressive residual stresses,grain refinement,increased grain boundaries,increased hardness,and increased static contact angle are the main factors related to the improvement of corrosion resistance in most materials,while increased roughness tends to weaken surface corrosion resistance.展开更多
The novel Co-based superalloys are extensively used in gas-powered and jet engine turbines due to their excellent high-temperature performance, achieved by strengthening the L12-γ′ ordered phase. This review present...The novel Co-based superalloys are extensively used in gas-powered and jet engine turbines due to their excellent high-temperature performance, achieved by strengthening the L12-γ′ ordered phase. This review presents an overview of the research progress on oxidation behavior of Co-based superalloys, including oxidation kinetics, oxides morphology, the formation and spallation of oxide layers, and importantly, the synergistic effects of alloying elements on oxidation resistance—a critical area considering the complex interactions with multiple alloying elements. Additionally, this review compares the oxidation resistance of single crystal versus polycrystalline alloys. The effect of phase interface and dislocations on oxidation behavior is also discussed. While significant progress has been achieved, areas necessitating further investigation include optimizing alloy compositions for enhanced oxidation resistance and understanding the long-term stability of oxide layers. The future prospects for Co-based superalloys are promising as ongoing research aims to address the existing challenges and unlock new applications at even higher operating temperatures.展开更多
The application of machine learning in alloy design is increasingly widespread,yet traditional models still face challenges when dealing with limited datasets and complex nonlinear relationships.This work proposes an ...The application of machine learning in alloy design is increasingly widespread,yet traditional models still face challenges when dealing with limited datasets and complex nonlinear relationships.This work proposes an interpretable machine learning method based on data augmentation and reconstruction,excavating high-performance low-alloyed magnesium(Mg)alloys.The data augmentation technique expands the original dataset through Gaussian noise.The data reconstruction method reorganizes and transforms the original data to extract more representative features,significantly improving the model's generalization ability and prediction accuracy,with a coefficient of determination(R^(2))of 95.9%for the ultimate tensile strength(UTS)model and a R^(2)of 95.3%for the elongation-to-failure(EL)model.The correlation coefficient assisted screening(CCAS)method is proposed to filter low-alloyed target alloys.A new Mg-2.2Mn-0.4Zn-0.2Al-0.2Ca(MZAX2000,wt%)alloy is designed and extruded into bar at given processing parameters,achieving room-temperature strength-ductility synergy showing an excellent UTS of 395 MPa and a high EL of 17.9%.This is closely related to its hetero-structured characteristic in the as-extruded MZAX2000 alloy consisting of coarse grains(16%),fine grains(75%),and fiber regions(9%).Therefore,this work offers new insights into optimizing alloy compositions and processing parameters for attaining new high strong and ductile low-alloyed Mg alloys.展开更多
To accurately diagnosemisfire faults in automotive engines,we propose a Channel Attention Convolutional Model,specifically the Squeeze-and-Excitation Networks(SENET),for classifying engine vibration signals and precis...To accurately diagnosemisfire faults in automotive engines,we propose a Channel Attention Convolutional Model,specifically the Squeeze-and-Excitation Networks(SENET),for classifying engine vibration signals and precisely pinpointing misfire faults.In the experiment,we established a total of 11 distinct states,encompassing the engine’s normal state,single-cylinder misfire faults,and dual-cylinder misfire faults for different cylinders.Data collection was facilitated by a highly sensitive acceleration signal collector with a high sampling rate of 20,840Hz.The collected data were methodically divided into training and testing sets based on different experimental groups to ensure generalization and prevent overlap between the two sets.The results revealed that,with a vibration acceleration sequence of 1000 time steps(approximately 50 ms)as input,the SENET model achieved a misfire fault detection accuracy of 99.8%.For comparison,we also trained and tested several commonly used models,including Long Short-Term Memory(LSTM),Transformer,and Multi-Scale Residual Networks(MSRESNET),yielding accuracy rates of 84%,79%,and 95%,respectively.This underscores the superior accuracy of the SENET model in detecting engine misfire faults compared to other models.Furthermore,the F1 scores for each type of recognition in the SENET model surpassed 0.98,outperforming the baseline models.Our analysis indicated that the misclassified samples in the LSTM and Transformer models’predictions were primarily due to intra-class misidentifications between single-cylinder and dual-cylinder misfire scenarios.To delve deeper,we conducted a visual analysis of the features extracted by the LSTM and SENET models using T-distributed Stochastic Neighbor Embedding(T-SNE)technology.The findings revealed that,in the LSTMmodel,data points of the same type tended to cluster together with significant overlap.Conversely,in the SENET model,data points of various types were more widely and evenly dispersed,demonstrating its effectiveness in distinguishing between different fault types.展开更多
Efficient lubrication of magnesium alloys is a highly challenging topic in the field of tribology.In this study,magnesium silicate hydroxide(MSH)nanotubes with serpentine structures were synthesized.The tribological b...Efficient lubrication of magnesium alloys is a highly challenging topic in the field of tribology.In this study,magnesium silicate hydroxide(MSH)nanotubes with serpentine structures were synthesized.The tribological behavior of AZ91D magnesium alloy rubbed against GCr15 steel was studied under lubricating oil with surface-modified MSH nanotubes as additives.The effects of the concentration,applied load,and reciprocating frequency on the friction and wear of the AZ91D alloy were studied using an SRV-4 sliding wear tester.Results show a decrease of 18.7–68.5%in friction coefficient,and a reduction of 19.4–54.3%in wear volume of magnesium alloy can be achieved by applying the synthetic serpentine additive under different conditions.A suspension containing 0.3 wt.%MSH was most efficient in reducing wear and friction.High frequency and medium load were more conducive to improving the tribological properties of magnesium alloys.A series of beneficial physical and chemical processes occurring at the AZ91D alloy/steel interface can be used to explain friction and wear reduction based on the characterization of the morphology,chemical composition,chemical state,microstructure,and nanomechanical properties of the worn surface.The synthetic MSH,with serpentine structure and nanotube morphology,possesses excellent adsorbability,high chemical activity,and good self-lubrication and catalytic activity.Therefore,physical polishing,tribochemical reactions,and physicalchemical depositions can occur easily on the sliding contacts.A dense tribolayer with a complex composition and composite structure was formed on the worn surface.Its high hardness,good toughness and plasticity,and prominent lubricity resulted in the improvement of friction and wear,making the synthetic MSH a promising efficient oil additive for magnesium alloys under boundary and mixed lubrication.展开更多
A coupled thermal-hydro-mechanical cohesive phase-field model for hydraulic fracturing in deep coal seams is presented.Heat exchange between the cold fluid and the hot rock is considered,and the thermal contribution t...A coupled thermal-hydro-mechanical cohesive phase-field model for hydraulic fracturing in deep coal seams is presented.Heat exchange between the cold fluid and the hot rock is considered,and the thermal contribution terms between the cold fluid and the hot rock are derived.Heat transfer obeys Fourier's law,and porosity is used to relate the thermodynamic parameters of the fracture and matrix domains.The net pressure difference between the fracture and the matrix is neglected,and thus the fluid flow is modeled by the unified fluid-governing equations.The evolution equations of porosity and Biot's coefficient during hydraulic fracturing are derived from their definitions.The effect of coal cleats is considered and modeled by Voronoi polygons,and this approach is shown to have high accuracy.The accuracy of the proposed model is verified by two sets of fracturing experiments in multilayer coal seams.Subsequently,the differences in fracture morphology,fluid pressure response,and fluid pressure distribution between direct fracturing of coal seams and indirect fracturing of shale interlayers are explored,and the effects of the cluster number and cluster spacing on fracture morphology for multi-cluster fracturing are also examined.The numerical results show that the proposed model is expected to be a powerful tool for the fracturing design and optimization of deep coalbed methane.展开更多
To verify the wear resistance and erosion resistance of Ti-doped Ta_(2)O_(5)coating(TTO),a series of TTOs were prepared by magnetron sputtering technology by controlling the power of the Ti target.The change of growth...To verify the wear resistance and erosion resistance of Ti-doped Ta_(2)O_(5)coating(TTO),a series of TTOs were prepared by magnetron sputtering technology by controlling the power of the Ti target.The change of growth structure,microstructure,and tribological properties of TTOs with Ti target power was studied.After the erosion test,the variation of erosion damage behavior of TTOs with mechanical properties under different erosion conditions was further studied.The results show that the TTOs eliminate the roughness,voids,and defects in the material due to the mobility of the adsorbed atoms during the growth process,and a flat and dense smooth surface is obtained.Tribological tests show that the TTOs are mainly characterized by plastic deformation and microcrack wear mechanism.Higher Ti target power can improve the wear resistance of TTOs.Erosion test results reveal that the impact crater,furrow,micro-cutting,brittle spalling,and crack formation are the main wear mechanisms of the TTOs samples under erosion conditions.展开更多
A high-temperature and high-pressure valve is the key equipment of a wind tunnel system;it controls the generation of high-temperature and high-pressure gas.To reduce the adverse impact of high-temperature and high-pr...A high-temperature and high-pressure valve is the key equipment of a wind tunnel system;it controls the generation of high-temperature and high-pressure gas.To reduce the adverse impact of high-temperature and high-pressure gas on the strength of the valve body,a cooling structure is set on the valve seat.This can significantly reduce the temperature of the valve body and valve seat.The effects of its structure on the cooling characteristics and stress of the valve seat are studied,and six main parameters that can completely describe the geometry of the cooling structure are proposed.The central composite design method is used to select sample points,and the multi-objective genetic algorithm(MOGA)method is used for optimal structural design.A modification method according to the main parameters for the valve seat is proposed.The results show that the cooling structure weakens the pressure-bearing capability of the valve seat.Among the six main parameters of the valve seat,the distance from the end face of the lower hole to the Z-axis and the distance from the axis of the lower hole to the origin of the coordinates have the most obvious effects on the average stress of the valve seat.An optimum design value is proposed.This work can provide a reference for the design of high-temperature and high-pressure valves.展开更多
To enhance the mechanical properties of Mo alloys prepared through laser powder bed fusion(LPBF),a hot isostatic pressing(HIP)treatment was used.Results show that following HIP treatment,the porosity decreases from 0....To enhance the mechanical properties of Mo alloys prepared through laser powder bed fusion(LPBF),a hot isostatic pressing(HIP)treatment was used.Results show that following HIP treatment,the porosity decreases from 0.27%to 0.22%,enabling the elements Mo and Ti to diffuse fully and to distribute more uniformly,and to forming a substantial number of low-angle grain boundaries.The tensile strength soars from 286±32 MPa to 598±22 MPa,while the elongation increases from 0.08%±0.02%to 0.18%±0.02%,without notable alterations in grain morphology during the tensile deformation.HIP treatment eliminates the molten pool boundaries,which are the primary source for premature failure in LPBFed Mo alloys.Consequently,HIP treatment emerges as a novel and effective approach for strengthening the mechanical properties of LPBFed Mo alloys,offering a fresh perspective on producing high-performance Mo-based alloys.展开更多
A low rare-earth containing ZEK100-O magnesium alloy was welded to AA1230-clad high-strength AA2024-T3 aluminum alloy via solidstate ultrasonic spot welding(USW)to evaluate the microstructure,tensile lap shear strengt...A low rare-earth containing ZEK100-O magnesium alloy was welded to AA1230-clad high-strength AA2024-T3 aluminum alloy via solidstate ultrasonic spot welding(USW)to evaluate the microstructure,tensile lap shear strength,and fatigue properties.The tensile strength increased with increasing welding energy,peaked at a welding energy of 1000 J,and then decreased due to the formation of an increasingly thick diffusion layer mainly containing Al12Mg17intermetallic compound at higher energy levels.The peak tensile lap shear strength attained at 1000 J was attributed to the optimal inter-diffusion between the magnesium alloy and softer AA1230-clad Al layer along with the presence of‘fishhook'-like mechanical interlocks at the weld interface and the formation of an indistinguishable intermetallic layer.The dissimilar joints welded at 1000 J also exhibited a longer fatigue life than other Mg-Al dissimilar joints,suggesting the beneficial role of the softer clad layer with a better intermingling capacity during USW.While the transverse-through-thickness(TTT)failure mode prevailed at lower cyclic loading levels,interfacial failure was the predominant mode of fatigue failure at higher cyclic loads,where distinctive fatigue striations were also observed on the fracture surface of the softer clad Al layer.This was associated with the presence of opening stress and bending moment near the nugget edge despite the tension-tension lap shear cyclic loading applied.展开更多
Accurate prediction of the remaining useful life(RUL)is crucial for the design and management of lithium-ion batteries.Although various machine learning models offer promising predictions,one critical but often overlo...Accurate prediction of the remaining useful life(RUL)is crucial for the design and management of lithium-ion batteries.Although various machine learning models offer promising predictions,one critical but often overlooked challenge is their demand for considerable run-to-failure data for training.Collection of such training data leads to prohibitive testing efforts as the run-to-failure tests can last for years.Here,we propose a semi-supervised representation learning method to enhance prediction accuracy by learning from data without RUL labels.Our approach builds on a sophisticated deep neural network that comprises an encoder and three decoder heads to extract time-dependent representation features from short-term battery operating data regardless of the existence of RUL labels.The approach is validated using three datasets collected from 34 batteries operating under various conditions,encompassing over 19,900 charge and discharge cycles.Our method achieves a root mean squared error(RMSE)within 25 cycles,even when only 1/50 of the training dataset is labelled,representing a reduction of 48%compared to the conventional approach.We also demonstrate the method's robustness with varying numbers of labelled data and different weights assigned to the three decoder heads.The projection of extracted features in low space reveals that our method effectively learns degradation features from unlabelled data.Our approach highlights the promise of utilising semi-supervised learning to reduce the data demand for reliability monitoring of energy devices.展开更多
基金This work was supported by the Deanship of Scientific Research,King Khalid University,Kingdom of Saudi Arabia under research Grant Number(R.G.P.2/100/41).
文摘Human Adaptive Mechatronics(HAM)includes human and computer system in a closed loop.Elderly person with disabilities,normally carry out their daily routines with some assistance to move their limbs.With the short fall of human care takers,mechatronics devices are used with the likes of exoskeleton and exosuits to assist them.The rehabilitation and occupational therapy equipments utilize the electromyography(EMG)signals to measure the muscle activity potential.This paper focuses on optimizing the HAM model in prediction of intended motion of upper limb with high accuracy and to increase the response time of the system.Limb characteristics extraction from EMG signal and prediction of optimal controller parameters are modeled.Time and frequency based approach of EMG signal are considered for feature extraction.The models used for estimating motion and muscle parameters from EMG signal for carrying out limb movement predictions are validated.Based on the extracted features,optimal parameters are selected by Modified Lion Optimization(MLO)for controlling the HAM system.Finally,supervised machine learning makes predictions at different points in time for individual sensing using Support Vector Neural Network(SVNN).This model is also evaluated based on optimal parameters of motion estimation and the accuracy level along with different optimization models for various upper limb movements.The proposed model of human adaptive controller predicts the limb movement by 96%accuracy.
基金Projects(51135009,51105371) supported by the National Natural Science Foundation of China
文摘LuGre model has been widely used in friction modeling and compensation.However,the new friction regime,named prestiction regime,cannot be accurately characterized by LuGre model in the latest research.With the extensive experimental observations of friction behaviors in the prestiction,some variables were abstracted to depict the rules in the prestiction regime.Based upon the knowledge of friction modeling,a novel friction model including the presliding regime,the gross sliding regime and the prestiction regime was then presented to overcome the shortcomings of the LuGre model.The reason that LuGre model cannot estimate the prestiction friction was analyzed in theory.Feasibility analysis of the proposed model in modeling the prestiction friction was also addressed.A parameter identification method for the proposed model based on multilevel coordinate search algorithm was presented.The proposed friction compensation strategy was composed of a nonlinear friction observer and a feedforward mechanism.The friction observer was designed to estimate the friction force in the presliding and the gross sliding regimes.And the friction force was estimated based on the model in the prestiction regime.The comparative trajectory tracking experiments were conducted on a simulator of inertially stabilization platforms among three control schemes:the single proportional–derivative(PD)control,the PD with LuGre model-based compensation and the PD with compensator based on the presented model.The experimental results reveal that the control scheme based on the proposed model has the best tracking performance.It reduces the peak-to-peak value(PPV)of tracking error to 0.2 mrad,which is improved almost 50%compared with the PD with LuGre model-based compensation.Compared to the single PD control,it reduces the PPV of error by 66.7%.
文摘Healthcare mechatronics is a typical multidisciplinary field involving machinery,medicine,computer,and automation,which has been widely applied in respiratory therapy,urology robot,rehabilitation exoskeleton,artificial heart,etc.Existing progresses has some defects in modeling,design and implementation of healthcare mechatronics.Therefore,exploring new design theories,key technologies and typical applications is an effective to promote the rapid development of this field.
基金National Natural Science Foundation of China(NSFC)supported this work under Grant No.32250410309,11674086,51736006,and 51772080funding from Science and Technology Department of Jiangsu Province under Grant No.BE2022029Shenzhen University under Grant No.86902/000248 also supported part of this work.
文摘The development of low-temperature solid oxide fuel cells(LT-SOFCs)is of significant importance for realizing the widespread application of SOFCs.This has stimulated a substantial materials research effort in developing high oxide-ion conductivity in the electrolyte layer of SOFCs.In this context,for the first time,a dielectric material,CaCu_(3)Ti_(4)O_(12)(CCTO)is designed for LT-SOFCs electrolyte application in this study.Both individual CCTO and its heterostructure materials with a p-type Ni_(0.8)Co_(0.15)Al_(0.05)LiO_(2−δ)(NCAL)semiconductor are evaluated as alternative electrolytes in LT-SOFC at 450–550℃.The single cell with the individual CCTO electrolyte exhibits a power output of approximately 263 mW cm^(-2) and an open-circuit voltage(OCV)of 0.95 V at 550℃,while the cell with the CCTO–NCAL heterostructure electrolyte capably delivers an improved power output of approximately 605 mW cm^(-2) along with a higher OCV over 1.0 V,which indicates the introduction of high hole-conducting NCAL into the CCTO could enhance the cell performance rather than inducing any potential short-circuiting risk.It is found that these promising outcomes are due to the interplay of the dielectric material,its structure,and overall properties that led to improve electrochemical mechanism in CCTO–NCAL.Furthermore,density functional theory calculations provide the detailed information about the electronic and structural properties of the CCTO and NCAL and their heterostructure CCTO–NCAL.Our study thus provides a new approach for developing new advanced electrolytes for LT-SOFCs.
基金National Natural Science Foundation of China(No.51705545)。
文摘The active sound absorption technique excels in mitigating low-frequency sound waves,yet it falls short when dealing with medium and high-frequency sound waves.To enhance the sound-absorbing effect of medium and high-frequency sound waves,a novel semi-active sound absorption method has been introduced.This method modulates the surface impedance of a loudspeaker positioned behind the sound-absorbing material,thereby altering the sound absorption coefficient.The theoretical sound absorption coefficient is calculated using MATLAB and compared with the experimental one.Results show that the method can effectively modulates the absorption coefficient in response to varying incident sound wave frequencies,ensuring that it remains at its peak value.
基金funded by the National Natural Science Foundation of China(Grant No.06101213)the National Natural Science Foundation of China(Grant No.22105160).
文摘3D printing technology enhances the combustion characteristics of hybrid rocket fuels by enabling complex geometries. However, improvements in regression rates and energy properties of monotonous 3D printed fuels have been limited. This study explores the impact of poly(vinylidene fluoride) and polydopamine-coated aluminum particles on the thermal and combustion properties of 3D printed hybrid rocket fuels. Physical self-assembly and anti-solvent methods were employed for constructing composite μAl particles. Characterization using SEM, XRD, XPS, FTIR, and μCT revealed a core-shell structure and homogeneous elemental distribution. Thermal analysis showed that PVDF coatings significantly increased the heat of combustion for aluminum particles, with maximum enhancement observed in μAl@PDA@PVDF(denoted as μAl@PF) at 6.20 k J/g. Subsequently, 3D printed fuels with varying pure and composite μAl particle contents were prepared using 3D printing. Combustion tests indicated higher regression rates for Al@PF/Resin composites compared to pure resin, positively correlating with particle content. The fluorocarbon-alumina reaction during the combustion stage intensified Al particle combustion, reducing residue size. A comprehensive model based on experiments provides insights into the combustion process of PDA and PVDF-coated droplets. This study advances the design of 3D-printed hybrid rocket fuels, offering strategies to improve regression rates and energy release, crucial for enhancing solid fuel performance for hybrid propulsion.
基金funded by the National Natural Science Foundation of China Youth Fund(Grant No.62304022)Science and Technology on Electromechanical Dynamic Control Laboratory(China,Grant No.6142601012304)the 2022e2024 China Association for Science and Technology Innovation Integration Association Youth Talent Support Project(Grant No.2022QNRC001).
文摘Metal Additive Manufacturing(MAM) technology has become an important means of rapid prototyping precision manufacturing of special high dynamic heterogeneous complex parts. In response to the micromechanical defects such as porosity issues, significant deformation, surface cracks, and challenging control of surface morphology encountered during the selective laser melting(SLM) additive manufacturing(AM) process of specialized Micro Electromechanical System(MEMS) components, multiparameter optimization and micro powder melt pool/macro-scale mechanical properties control simulation of specialized components are conducted. The optimal parameters obtained through highprecision preparation and machining of components and static/high dynamic verification are: laser power of 110 W, laser speed of 600 mm/s, laser diameter of 75 μm, and scanning spacing of 50 μm. The density of the subordinate components under this reference can reach 99.15%, the surface hardness can reach 51.9 HRA, the yield strength can reach 550 MPa, the maximum machining error of the components is 4.73%, and the average surface roughness is 0.45 μm. Through dynamic hammering and high dynamic firing verification, SLM components meet the requirements for overload resistance. The results have proven that MEM technology can provide a new means for the processing of MEMS components applied in high dynamic environments. The parameters obtained in the conclusion can provide a design basis for the additive preparation of MEMS components.
基金supported by the Major Science and Technology Project of Zhongshan City(No.2022AJ004)the Key Basic and Applied Research Program of Guangdong Province(Nos.2019B030302010 and 2022B1515120082)Guangdong Science and Technology Innovation Project(No.2021TX06C111).
文摘In general,the rapid growth of α-Fe clusters is a challenge in high Fe-content Fe-based amorphous alloys,negatively affecting their physical properties.Herein,we introduce an efficient and rapid post-treatment technique known as ultrasonic vibration rapid processing(UVRP),which enables the formation of high-density strong magnetic α-Fe clusters,thereby enhancing the soft magnetic properties of Fe_(78)Si(13)B_(9) amorphous alloy ribbon.
基金supported by the National Natural Science Foundation of China(52475610)Zhejiang Provincial Natural Science Foundation of China(LDQ24E050001).
文摘Despite the promising progress in conductive hydrogels made with pure conducting polymer,great challenges remain in the interface adhesion and robustness in longterm monitoring.To address these challenges,Prof.Seung Hwan Ko and Taek-Soo Kim’s team introduced a laserinduced phase separation and adhesion method for fabricating conductive hydrogels consisting of pure poly(3,4-ethylenedioxythiophene):polystyrene sulfonate on polymer substrates.The laser-induced phase separation and adhesion treated conducting polymers can be selectively transformed into conductive hydrogels that exhibit wet conductivities of 101.4 S cm^(−1) with a spatial resolution down to 5μm.Moreover,they maintain impedance and charge-storage capacity even after 1 h of sonication.The micropatterned electrode arrays demonstrate their potential in long-term in vivo signal recordings,highlighting their promising role in the field of bioelectronics.
基金Introduction of Talent Research Start-up Fund of Anhui University of Science and Technology(2022yjrc35)Colleges and Universities Excellent Young Talents Domestic Visit Research Project of Anhui Province(gxgnfx2022006)。
文摘According to surface morphology,microhardness,X-ray diffraction,and static contact angle experiments,the changes in the surface integrity and corrosion resistance of 6061-T6 aluminum alloy after ultrasonic shot peening(USP)were investigated.Results show that the grain size of the material surface is reduced by 43%,the residual compressive stress has an increasing trend,the roughness and hardness are increased by approximately 211.1%and 35%,respectively.And the static contact angle is increased at first,followed by a slight decrease.Weighing,scanning electron microscope,and energy dispersive spectrometer were used to study the samples after a cyclic corrosion test.Results show that USP reduces the corrosion rate by 41.2%.A model of surface corrosion mechanism of USP is developed,and the mechanism of USP to improve the corrosion resistance of materials is discussed.The introduction of compressive residual stresses,grain refinement,increased grain boundaries,increased hardness,and increased static contact angle are the main factors related to the improvement of corrosion resistance in most materials,while increased roughness tends to weaken surface corrosion resistance.
基金support from the National Natural Science Foundation of China(Nos.52171107,52201203)the Hebei Provincial Natural Science Foundation,China(No.E2021501026)the National Natural Science Foundation of China-Joint Fund of Iron and Steel Research(No.U1960204).
文摘The novel Co-based superalloys are extensively used in gas-powered and jet engine turbines due to their excellent high-temperature performance, achieved by strengthening the L12-γ′ ordered phase. This review presents an overview of the research progress on oxidation behavior of Co-based superalloys, including oxidation kinetics, oxides morphology, the formation and spallation of oxide layers, and importantly, the synergistic effects of alloying elements on oxidation resistance—a critical area considering the complex interactions with multiple alloying elements. Additionally, this review compares the oxidation resistance of single crystal versus polycrystalline alloys. The effect of phase interface and dislocations on oxidation behavior is also discussed. While significant progress has been achieved, areas necessitating further investigation include optimizing alloy compositions for enhanced oxidation resistance and understanding the long-term stability of oxide layers. The future prospects for Co-based superalloys are promising as ongoing research aims to address the existing challenges and unlock new applications at even higher operating temperatures.
基金funded by the National Natural Science Foundation of China(No.52204407)the Natural Science Foundation of Jiangsu Province(No.BK20220595)+1 种基金the China Postdoctoral Science Foundation(No.2022M723689)the Industrial Collaborative Innovation Project of Shanghai(No.XTCX-KJ-2022-2-11)。
文摘The application of machine learning in alloy design is increasingly widespread,yet traditional models still face challenges when dealing with limited datasets and complex nonlinear relationships.This work proposes an interpretable machine learning method based on data augmentation and reconstruction,excavating high-performance low-alloyed magnesium(Mg)alloys.The data augmentation technique expands the original dataset through Gaussian noise.The data reconstruction method reorganizes and transforms the original data to extract more representative features,significantly improving the model's generalization ability and prediction accuracy,with a coefficient of determination(R^(2))of 95.9%for the ultimate tensile strength(UTS)model and a R^(2)of 95.3%for the elongation-to-failure(EL)model.The correlation coefficient assisted screening(CCAS)method is proposed to filter low-alloyed target alloys.A new Mg-2.2Mn-0.4Zn-0.2Al-0.2Ca(MZAX2000,wt%)alloy is designed and extruded into bar at given processing parameters,achieving room-temperature strength-ductility synergy showing an excellent UTS of 395 MPa and a high EL of 17.9%.This is closely related to its hetero-structured characteristic in the as-extruded MZAX2000 alloy consisting of coarse grains(16%),fine grains(75%),and fiber regions(9%).Therefore,this work offers new insights into optimizing alloy compositions and processing parameters for attaining new high strong and ductile low-alloyed Mg alloys.
基金Yongxian Huang supported by Projects of Guangzhou Science and Technology Plan(2023A04J0409)。
文摘To accurately diagnosemisfire faults in automotive engines,we propose a Channel Attention Convolutional Model,specifically the Squeeze-and-Excitation Networks(SENET),for classifying engine vibration signals and precisely pinpointing misfire faults.In the experiment,we established a total of 11 distinct states,encompassing the engine’s normal state,single-cylinder misfire faults,and dual-cylinder misfire faults for different cylinders.Data collection was facilitated by a highly sensitive acceleration signal collector with a high sampling rate of 20,840Hz.The collected data were methodically divided into training and testing sets based on different experimental groups to ensure generalization and prevent overlap between the two sets.The results revealed that,with a vibration acceleration sequence of 1000 time steps(approximately 50 ms)as input,the SENET model achieved a misfire fault detection accuracy of 99.8%.For comparison,we also trained and tested several commonly used models,including Long Short-Term Memory(LSTM),Transformer,and Multi-Scale Residual Networks(MSRESNET),yielding accuracy rates of 84%,79%,and 95%,respectively.This underscores the superior accuracy of the SENET model in detecting engine misfire faults compared to other models.Furthermore,the F1 scores for each type of recognition in the SENET model surpassed 0.98,outperforming the baseline models.Our analysis indicated that the misclassified samples in the LSTM and Transformer models’predictions were primarily due to intra-class misidentifications between single-cylinder and dual-cylinder misfire scenarios.To delve deeper,we conducted a visual analysis of the features extracted by the LSTM and SENET models using T-distributed Stochastic Neighbor Embedding(T-SNE)technology.The findings revealed that,in the LSTMmodel,data points of the same type tended to cluster together with significant overlap.Conversely,in the SENET model,data points of various types were more widely and evenly dispersed,demonstrating its effectiveness in distinguishing between different fault types.
基金support from the National Natural Science Foundation of China(grant number 52075544)Innovation Funds of Jihua Laboratory(X220971UZ230)+1 种基金Basic and Applied Basic Research Foundation of Guangdong Province(2022A1515110649)Funds from Research Platforms of Guangdong Higher Education Institutes(2022ZDJS038).
文摘Efficient lubrication of magnesium alloys is a highly challenging topic in the field of tribology.In this study,magnesium silicate hydroxide(MSH)nanotubes with serpentine structures were synthesized.The tribological behavior of AZ91D magnesium alloy rubbed against GCr15 steel was studied under lubricating oil with surface-modified MSH nanotubes as additives.The effects of the concentration,applied load,and reciprocating frequency on the friction and wear of the AZ91D alloy were studied using an SRV-4 sliding wear tester.Results show a decrease of 18.7–68.5%in friction coefficient,and a reduction of 19.4–54.3%in wear volume of magnesium alloy can be achieved by applying the synthetic serpentine additive under different conditions.A suspension containing 0.3 wt.%MSH was most efficient in reducing wear and friction.High frequency and medium load were more conducive to improving the tribological properties of magnesium alloys.A series of beneficial physical and chemical processes occurring at the AZ91D alloy/steel interface can be used to explain friction and wear reduction based on the characterization of the morphology,chemical composition,chemical state,microstructure,and nanomechanical properties of the worn surface.The synthetic MSH,with serpentine structure and nanotube morphology,possesses excellent adsorbability,high chemical activity,and good self-lubrication and catalytic activity.Therefore,physical polishing,tribochemical reactions,and physicalchemical depositions can occur easily on the sliding contacts.A dense tribolayer with a complex composition and composite structure was formed on the worn surface.Its high hardness,good toughness and plasticity,and prominent lubricity resulted in the improvement of friction and wear,making the synthetic MSH a promising efficient oil additive for magnesium alloys under boundary and mixed lubrication.
基金Project supported by the National Natural Science Foundation of China(No.42202314)。
文摘A coupled thermal-hydro-mechanical cohesive phase-field model for hydraulic fracturing in deep coal seams is presented.Heat exchange between the cold fluid and the hot rock is considered,and the thermal contribution terms between the cold fluid and the hot rock are derived.Heat transfer obeys Fourier's law,and porosity is used to relate the thermodynamic parameters of the fracture and matrix domains.The net pressure difference between the fracture and the matrix is neglected,and thus the fluid flow is modeled by the unified fluid-governing equations.The evolution equations of porosity and Biot's coefficient during hydraulic fracturing are derived from their definitions.The effect of coal cleats is considered and modeled by Voronoi polygons,and this approach is shown to have high accuracy.The accuracy of the proposed model is verified by two sets of fracturing experiments in multilayer coal seams.Subsequently,the differences in fracture morphology,fluid pressure response,and fluid pressure distribution between direct fracturing of coal seams and indirect fracturing of shale interlayers are explored,and the effects of the cluster number and cluster spacing on fracture morphology for multi-cluster fracturing are also examined.The numerical results show that the proposed model is expected to be a powerful tool for the fracturing design and optimization of deep coalbed methane.
文摘To verify the wear resistance and erosion resistance of Ti-doped Ta_(2)O_(5)coating(TTO),a series of TTOs were prepared by magnetron sputtering technology by controlling the power of the Ti target.The change of growth structure,microstructure,and tribological properties of TTOs with Ti target power was studied.After the erosion test,the variation of erosion damage behavior of TTOs with mechanical properties under different erosion conditions was further studied.The results show that the TTOs eliminate the roughness,voids,and defects in the material due to the mobility of the adsorbed atoms during the growth process,and a flat and dense smooth surface is obtained.Tribological tests show that the TTOs are mainly characterized by plastic deformation and microcrack wear mechanism.Higher Ti target power can improve the wear resistance of TTOs.Erosion test results reveal that the impact crater,furrow,micro-cutting,brittle spalling,and crack formation are the main wear mechanisms of the TTOs samples under erosion conditions.
基金supported by the National Natural Science Foundation of China(No.52175067)the Zhejiang Key Research&Development Project(No.2021C01021)+1 种基金the Natural Science Foundation of Zhejiang Province(No.LY20E050016)the Postdoctoral Fellowship Program of China Postdoctoral Science Foundation(CPSF)(No.GZC20241478)。
文摘A high-temperature and high-pressure valve is the key equipment of a wind tunnel system;it controls the generation of high-temperature and high-pressure gas.To reduce the adverse impact of high-temperature and high-pressure gas on the strength of the valve body,a cooling structure is set on the valve seat.This can significantly reduce the temperature of the valve body and valve seat.The effects of its structure on the cooling characteristics and stress of the valve seat are studied,and six main parameters that can completely describe the geometry of the cooling structure are proposed.The central composite design method is used to select sample points,and the multi-objective genetic algorithm(MOGA)method is used for optimal structural design.A modification method according to the main parameters for the valve seat is proposed.The results show that the cooling structure weakens the pressure-bearing capability of the valve seat.Among the six main parameters of the valve seat,the distance from the end face of the lower hole to the Z-axis and the distance from the axis of the lower hole to the origin of the coordinates have the most obvious effects on the average stress of the valve seat.An optimum design value is proposed.This work can provide a reference for the design of high-temperature and high-pressure valves.
基金National Natural Science Foundation of China(52105385)Stable Support Plan Program of Shenzhen Natural Science Fund(20220810132537001)+2 种基金Guangdong Basic and Applied Basic Research Foundation(2022A1515010781)Joint Fund of Henan Province Science and Technology R&D Program(225200810002)Fundamental Research Funds of Henan Academy of Sciences(240621041)。
文摘To enhance the mechanical properties of Mo alloys prepared through laser powder bed fusion(LPBF),a hot isostatic pressing(HIP)treatment was used.Results show that following HIP treatment,the porosity decreases from 0.27%to 0.22%,enabling the elements Mo and Ti to diffuse fully and to distribute more uniformly,and to forming a substantial number of low-angle grain boundaries.The tensile strength soars from 286±32 MPa to 598±22 MPa,while the elongation increases from 0.08%±0.02%to 0.18%±0.02%,without notable alterations in grain morphology during the tensile deformation.HIP treatment eliminates the molten pool boundaries,which are the primary source for premature failure in LPBFed Mo alloys.Consequently,HIP treatment emerges as a novel and effective approach for strengthening the mechanical properties of LPBFed Mo alloys,offering a fresh perspective on producing high-performance Mo-based alloys.
基金the National Natural Science Foundation of China(Grant No.51971183)supported by OU(Osaka University,Japan)program for multilateral international collaboration research in joining and welding。
文摘A low rare-earth containing ZEK100-O magnesium alloy was welded to AA1230-clad high-strength AA2024-T3 aluminum alloy via solidstate ultrasonic spot welding(USW)to evaluate the microstructure,tensile lap shear strength,and fatigue properties.The tensile strength increased with increasing welding energy,peaked at a welding energy of 1000 J,and then decreased due to the formation of an increasingly thick diffusion layer mainly containing Al12Mg17intermetallic compound at higher energy levels.The peak tensile lap shear strength attained at 1000 J was attributed to the optimal inter-diffusion between the magnesium alloy and softer AA1230-clad Al layer along with the presence of‘fishhook'-like mechanical interlocks at the weld interface and the formation of an indistinguishable intermetallic layer.The dissimilar joints welded at 1000 J also exhibited a longer fatigue life than other Mg-Al dissimilar joints,suggesting the beneficial role of the softer clad layer with a better intermingling capacity during USW.While the transverse-through-thickness(TTT)failure mode prevailed at lower cyclic loading levels,interfacial failure was the predominant mode of fatigue failure at higher cyclic loads,where distinctive fatigue striations were also observed on the fracture surface of the softer clad Al layer.This was associated with the presence of opening stress and bending moment near the nugget edge despite the tension-tension lap shear cyclic loading applied.
基金supported by the National Natural Science Foundation of China(No.52207229)the Key Research and Development Program of Ningxia Hui Autonomous Region of China(No.2024BEE02003)+1 种基金the financial support from the AEGiS Research Grant 2024,University of Wollongong(No.R6254)the financial support from the China Scholarship Council(No.202207550010).
文摘Accurate prediction of the remaining useful life(RUL)is crucial for the design and management of lithium-ion batteries.Although various machine learning models offer promising predictions,one critical but often overlooked challenge is their demand for considerable run-to-failure data for training.Collection of such training data leads to prohibitive testing efforts as the run-to-failure tests can last for years.Here,we propose a semi-supervised representation learning method to enhance prediction accuracy by learning from data without RUL labels.Our approach builds on a sophisticated deep neural network that comprises an encoder and three decoder heads to extract time-dependent representation features from short-term battery operating data regardless of the existence of RUL labels.The approach is validated using three datasets collected from 34 batteries operating under various conditions,encompassing over 19,900 charge and discharge cycles.Our method achieves a root mean squared error(RMSE)within 25 cycles,even when only 1/50 of the training dataset is labelled,representing a reduction of 48%compared to the conventional approach.We also demonstrate the method's robustness with varying numbers of labelled data and different weights assigned to the three decoder heads.The projection of extracted features in low space reveals that our method effectively learns degradation features from unlabelled data.Our approach highlights the promise of utilising semi-supervised learning to reduce the data demand for reliability monitoring of energy devices.
