This study evaluates the Fuzzy Analytical Hierarchy Process(FAHP)as a multi-criteria decision(MCD)support tool for selecting appropriate additive manufacturing(AM)techniques that align with cleaner production and envi...This study evaluates the Fuzzy Analytical Hierarchy Process(FAHP)as a multi-criteria decision(MCD)support tool for selecting appropriate additive manufacturing(AM)techniques that align with cleaner production and environmental sustainability.The FAHP model was validated using an example of the production of aircraft components(specifically fuselage)employing AM technologies such as Wire Arc Additive Manufacturing(WAAM),laser powder bed fusion(L-PBF),Binder Jetting(BJ),Selective Laser Sintering(SLS),and Laser Metal Deposition(LMD).The selection criteria prioritized eco-friendly manufacturing considerations,including the quality and properties of the final product(e.g.,surface finish,high strength,and corrosion resistance),service and functional requirements,weight reduction for improved energy efficiency(lightweight structures),and environmental responsibility.Sustainability metrics,such as cost-effectiveness,material efficiency,waste minimization,and environmental impact,are central to the evaluation process.A computer-aided modeling approach was also used to simulate the performance of aluminum(AA7075 T6),steel(304),and titanium alloy(Ti6Al4V)for fuselage development.The results demonstrate that MCD approaches such as FAHP can effectively guide the selection of AM technologies that meet functional and technical requirements while minimizing environmental degradation footprints.Furthermore,the aluminumalloy outperformed the other materials investigated in the simulation with the lowest stress concentration and least deformation.This study contributes to advancing cleaner production practices by providing a decision-making framework for sustainable and eco-friendly manufacturing,enabling manufacturers to adopt AM technologies that promote environmental responsibility and sustainable development,while maintaining product quality and performance.展开更多
The Industrial Internet of Things(IIoT)has brought numerous benefits,such as improved efficiency,smart analytics,and increased automation.However,it also exposes connected devices,users,applications,and data generated...The Industrial Internet of Things(IIoT)has brought numerous benefits,such as improved efficiency,smart analytics,and increased automation.However,it also exposes connected devices,users,applications,and data generated to cyber security threats that need to be addressed.This work investigates hybrid cyber threats(HCTs),which are now working on an entirely new level with the increasingly adopted IIoT.This work focuses on emerging methods to model,detect,and defend against hybrid cyber attacks using machine learning(ML)techniques.Specifically,a novel ML-based HCT modelling and analysis framework was proposed,in which L1 regularisation and Random Forest were used to cluster features and analyse the importance and impact of each feature in both individual threats and HCTs.A grey relation analysis-based model was employed to construct the correlation between IIoT components and different threats.展开更多
The metal-organic framework(MOF)derived Ni–Co–C–N composite alloys(NiCCZ)were“embedded”inside the carbon cloth(CC)strands as opposed to the popular idea of growing them upward to realize ultrastable energy storag...The metal-organic framework(MOF)derived Ni–Co–C–N composite alloys(NiCCZ)were“embedded”inside the carbon cloth(CC)strands as opposed to the popular idea of growing them upward to realize ultrastable energy storage and conversion application.The NiCCZ was then oxygen functionalized,facilitating the next step of stoichiometric sulfur anion diffusion during hydrothermal sulfurization,generating a flower-like metal hydroxysulfide structure(NiCCZOS)with strong partial implantation inside CC.Thus obtained NiCCZOS shows an excellent capacity when tested as a supercapacitor electrode in a three-electrode configuration.Moreover,when paired with the biomass-derived nitrogen-rich activated carbon,the asymmetric supercapacitor device shows almost 100%capacity retention even after 45,000 charge–discharge cycles with remarkable energy density(59.4 Wh kg^(-1)/263.8μWh cm^(–2))owing to a uniquely designed cathode.Furthermore,the same electrode performed as an excellent bifunctional water-splitting electrocatalyst with an overpotential of 271 mV for oxygen evolution reaction(OER)and 168.4 mV for hydrogen evolution reaction(HER)at 10 mA cm−2 current density along with 30 h of unhinged chronopotentiometric stability performance for both HER and OER.Hence,a unique metal chalcogenide composite electrode/substrate configuration has been proposed as a highly stable electrode material for flexible energy storage and conversion applications.展开更多
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
Innovative definitions of the electric and magnetic diffusivities through conducting mediums and innovative diffusion equations of the electric charges and magnetic flux are verified in this article. Such innovations ...Innovative definitions of the electric and magnetic diffusivities through conducting mediums and innovative diffusion equations of the electric charges and magnetic flux are verified in this article. Such innovations depend on the analogy of the governing laws of diffusion of the thermal, electrical, and magnetic energies and newly defined natures of the electric charges and magnetic flux as energy, or as electromagnetic waves, that have electric and magnetic potentials. The introduced diffusion equations of the electric charges and magnetic flux involve Laplacian operator and the introduced diffusivities. Both equations are applied to determine the electric and magnetic fields in conductors as the heat diffusion equation which is applied to determine the thermal field in steady and unsteady heat diffusion conditions. The use of electric networks for experimental modeling of thermal networks represents sufficient proof of similarity of the diffusion equations of both fields. By analysis of the diffusion phenomena of the three considered modes of energy transfer;the rates of flow of these energies are found to be directly proportional to the gradient of their volumetric concentration, or density, and the proportionality constants in such relations are the diffusivity of each energy. Such analysis leads also to find proportionality relations between the potentials of such energies and their volumetric concentrations. Validity of the introduced diffusion equations is verified by correspondence their solutions to the measurement results of the electric and magnetic fields in microwave ovens.展开更多
Precise and robust three-dimensional object detection(3DOD)presents a promising opportunity in the field of mobile robot(MR)navigation.Monocular 3DOD techniques typically involve extending existing twodimensional obje...Precise and robust three-dimensional object detection(3DOD)presents a promising opportunity in the field of mobile robot(MR)navigation.Monocular 3DOD techniques typically involve extending existing twodimensional object detection(2DOD)frameworks to predict the three-dimensional bounding box(3DBB)of objects captured in 2D RGB images.However,these methods often require multiple images,making them less feasible for various real-time scenarios.To address these challenges,the emergence of agile convolutional neural networks(CNNs)capable of inferring depth froma single image opens a new avenue for investigation.The paper proposes a novel ELDENet network designed to produce cost-effective 3DBounding Box Estimation(3D-BBE)froma single image.This novel framework comprises the PP-LCNet as the encoder and a fast convolutional decoder.Additionally,this integration includes a Squeeze-Exploit(SE)module utilizing the Math Kernel Library for Deep Neural Networks(MKLDNN)optimizer to enhance convolutional efficiency and streamline model size during effective training.Meanwhile,the proposed multi-scale sub-pixel decoder generates high-quality depth maps while maintaining a compact structure.Furthermore,the generated depthmaps provide a clear perspective with distance details of objects in the environment.These depth insights are combined with 2DOD for precise evaluation of 3D Bounding Boxes(3DBB),facilitating scene understanding and optimal route planning for mobile robots.Based on the estimated object center of the 3DBB,the Deep Reinforcement Learning(DRL)-based obstacle avoidance strategy for MRs is developed.Experimental results demonstrate that our model achieves state-of-the-art performance across three datasets:NYU-V2,KITTI,and Cityscapes.Overall,this framework shows significant potential for adaptation in intelligent mechatronic systems,particularly in developing knowledge-driven systems for mobile robot navigation.展开更多
The gantry crane system is a crucial equipment for loading and unloading containers at the shore site.The existing trend of crane technology is in the transition from in-site operators to remote operators outside the ...The gantry crane system is a crucial equipment for loading and unloading containers at the shore site.The existing trend of crane technology is in the transition from in-site operators to remote operators outside the cargo handling site,which will comply with all safety regulations,including conditional crane monitoring.However,remote control introduces certain drawbacks in machine maintenance,as no on-site operators can provide real-time feedback on abnormalities.Therefore,this study proposes a failure detection system that uses vibratory sensors installed on machines to monitor and provide early warnings for various failures.For faulty event identification,the Fast Fourier Transform is carried out for the raw vibratory signals,and several frequency bands are classified by using t-SNE to evaluate the significance among clusters.The adjustment of hyperparameters of the t-SNE will alter the quality of the classification of different events,and this process is conventionally operated in accordance with users’experience.In this study,we propose a novel rating approach to automatically tune the hyperparameters of t-SNE to evaluate the separation and cluster compactness of the t-SNE results.Then,the results of clusters served as input features for training the faulty event detection model,and the detection model shows more than 95%accuracy in identifying different abnormal conditions of the main hosting motor.展开更多
This paper presents the rigorous study of mobile robot navigation techniques used so far.The step by step investigations of classical and reactive approaches are made here to understand the development of path plannin...This paper presents the rigorous study of mobile robot navigation techniques used so far.The step by step investigations of classical and reactive approaches are made here to understand the development of path planning strategies in various environmental conditions and to identify research gap.The classical approaches such as cell decomposition(CD),roadmap approach(RA),artificial potential field(APF);reactive approaches such as genetic algorithm(GA),fuzzy logic(FL),neural network(NN),firefly algorithm(FA),particle swarm optimization(PSO),ant colony optimization(ACO),bacterial foraging optimization(BFO),artificial bee colony(ABC),cuckoo search(CS),shuffled frog leaping algorithm(SFLA)and other miscellaneous algorithms(OMA)are considered for study.The navigation over static and dynamic condition is analyzed(for single and multiple robot systems)and it has been observed that the reactive approaches are more robust and perform well in all terrain when compared to classical approaches.It is also observed that the reactive approaches are used to improve the performance of the classical approaches as a hybrid algorithm.Hence,reactive approaches are more popular and widely used for path planning of mobile robot.The paper concludes with tabular data and charts comparing the frequency of individual navigational strategies which can be used for specific application in robotics.展开更多
Thermal deformation of aluminum alloy casting materials for manufacturing the tire mold was numerically investigated.The AC7A and AC4C casting material was selected as casting material and the metal casting device was...Thermal deformation of aluminum alloy casting materials for manufacturing the tire mold was numerically investigated.The AC7A and AC4C casting material was selected as casting material and the metal casting device was used in order to manufacture the mold product of automobile tire in the actual industrial field.The temperature distribution and the cooling time of casting materials were numerically calculated by finite element analysis (FEA).Also,the thermal deformation such as displacement and stress distribution was calculated from the temperature results.The thermal deformation was closely related to the temperature difference between the surface and inside of the casting.The numerical analysis results reveal that the thermal deformation of AC7A casting material is higher than that of AC4C casting material.Also,the thermal deformation results at the central part are larger than that on the side of casting because of the shrinkage caused by the cooling speed difference.展开更多
Horizontal axis wind turbines are some of the most widely used clean energy generators in the world.Horizontal axis wind turbine blades need to be designed for optimization in order to maximize efficiency and simultan...Horizontal axis wind turbines are some of the most widely used clean energy generators in the world.Horizontal axis wind turbine blades need to be designed for optimization in order to maximize efficiency and simultaneously minimize the cost of energy.This work presents the optimization of new MEXICO blades for a horizontal axis wind turbine at the wind speed of 10 m/s.The optimization problem is posed to maximize the power coefficient while the design variables are twist angles on the blade radius and rotating axis positions on a chord length of the airfoils.Computational fluid dynamics was used for the aerodynamic simulation.Surrogate-assisted optimization was applied to reduce computational time.A surrogate model called a Kriging model,using a Gaussian correlation function along with various regression models,was applied while a genetic algorithm was used as an optimizer.The results obtained in this study are discussed and compared with those obtained from the original model.It was found that the Kriging model with linear regression gives better results than the Kriging model with second-order polynomial regression.The optimum blade obtained in this study showed better performance than the original blade at a low wind speed of 10 m/s.展开更多
This paper surveys the recent advances on the modeling and control of hysteresis of piezoelectric actuators(PTAs)in the context of high precision applications of atomic force microscopes(AFMs).The current states,findi...This paper surveys the recent advances on the modeling and control of hysteresis of piezoelectric actuators(PTAs)in the context of high precision applications of atomic force microscopes(AFMs).The current states,findings,and outcomes on hysteresis modeling and control in terms of achievable bandwidth and accuracy are discussed in detailed.Future challenges and the scope of possible research are presented to pave the way to video rate atomic force microscopy.展开更多
Friction stir welding（FSW） is a solid state joining technique developed to join high strength aluminum alloys and various ceramic reinforced metal matrix composites（MMCs）.FSW produces sound welds in MMCs without a...Friction stir welding（FSW） is a solid state joining technique developed to join high strength aluminum alloys and various ceramic reinforced metal matrix composites（MMCs）.FSW produces sound welds in MMCs without any deleterious reaction between reinforcement and matrix.The present work focused on the effect of FSW parameters on the tensile strength of Al-B4C composite joints.The central composite design of four factors and five levels was used to control the number of experiments.A mathematical model was developed to analyze the influence of FSW parameters.The results indicated that the joint fabricated using rotational speed of 1000 r/min,welding speed of 1.3 mm/s,axial force of 10 kN and the reinforcement of 12% showed larger tensile strength compared with the other joints.The developed model was optimized to maximize the tensile strength using generalized reduced gradient method.The metallographic analysis of the joints showed the presence of various zones such as weld nugget（WN） zone,thermo mechanically affected zone（TMAZ） and heat affected zone（HAZ）.The substantial grain refinement of aluminum matrix as well as significant size reduction of B4C particles was observed in the weld nugget.TMAZ was plastically deformed,thermally affected and exhibited elongated aluminum grains.展开更多
In order to provide data for joints control of our recently designed crucian hke biomlmetlc robot fish, an A-ray photograph technology was adopted to determine the number and length of vertebral joints. A frame-by-fra...In order to provide data for joints control of our recently designed crucian hke biomlmetlc robot fish, an A-ray photograph technology was adopted to determine the number and length of vertebral joints. A frame-by-frame analysis of high-speed videotapes was conducted to quantify the kinematics of crucian at four speeds （12.651 cm·s^-1, 18.201 cm·s^-1, 21.901 cm·s^-1, 24.368cm·s^-1） during cruising. In addition to a brief introduction to experimental conditions and methods, we analyzed the influence of individual diversity on the absolute length as well as the non-dimensional length of vertebral joints. We also presented the maximal angular velocity and acceleration of vertebral joints under four swimming speeds, and provided the change of relative rotation angle, angular difference, angular velocity and angular acceleration of the rear vertebral joints with time at a certain swimming speed of 12.651 cm·s^-1. At last, we presented the maximal lateral displacement of each mark at that speed. The study found that the influence of individual diversity on the non-dimensional length of vertebral joints is not significant; the maximal angular velocity and acceleration of vertebral joints increase with swimming speed; angular difference, angular velocity and angular acceleration exhibit two maximal values over one period at a certain swimming speed.展开更多
This paper reports the effect of friction stir welding （FSW） process parameters on tensile strength of cast LM6 aluminium alloy. Joints were made by using different combinations of tool rotation speed, welding speed...This paper reports the effect of friction stir welding （FSW） process parameters on tensile strength of cast LM6 aluminium alloy. Joints were made by using different combinations of tool rotation speed, welding speed and axial force each at four levels. The quality of weld zone was investigated using macrostructure and microstructure analysis. Tensile strength of the joints were evaluated and correlated with the weld zone hardness and microstructure. The joint fabricated using a rotational speed of 900 r/min, a welding speed of 75 mm/min and an axial force of 3 kN showed superior tensile strength compared with other joints. The tensile strength and microhardness of the welded joints for the optimum conditions were 166 MPa and 64.8 Hv respectively.展开更多
Nowadays,quadcopters are presented in many life applications which require the performance of automatic takeoff,trajectory tracking,and automatic landing.Thus,researchers are aiming to enhance the performance of these...Nowadays,quadcopters are presented in many life applications which require the performance of automatic takeoff,trajectory tracking,and automatic landing.Thus,researchers are aiming to enhance the performance of these vehicles through low-cost sensing solutions and the design of executable and robust control techniques.Due to high nonlinearities,strong couplings and under-actuation,the control design process of a quadcopter is a rather challenging task.Therefore,the main objective of this work is demonstrated through two main aspects.The first is the design of an adaptive neuro-fuzzy inference system(ANFIS)controller to develop the attitude and altitude of a quadcopter.The second is to create a systematic framework for implementing flight controllers in embedded systems.A suitable model of the quadcopter is also developed by taking into account aerodynamics effects.To show the effectiveness of the ANFIS approach,the performance of a well-trained ANFIS controller is compared to a classical proportional-derivative(PD)controller and a properly tuned fuzzy logic controller.The controllers are compared and tested under several different flight conditions including the capability to reject external disturbances.In the first stage,performance evaluation takes place in a nonlinear simulation environment.Then,the ANFIS-based controllers alongside attitude and position estimators,and precision landing algorithms are implemented for executions in a real-time autopilot.In precision landing systems,an IR-camera is used to detect an IR-beacon on the ground for precise positioning.Several flight tests of a quadcopter are conducted for results validation.Both simulations and experiments demonstrated superior results for quadcopter stability in different flight scenarios.展开更多
Cavitation bubble collapse has a great influence on the temperature of hydraulic oil. Herein, cone-type throttle valve experiments are carried out to study the thermodynamic processes of cavitation. First, the process...Cavitation bubble collapse has a great influence on the temperature of hydraulic oil. Herein, cone-type throttle valve experiments are carried out to study the thermodynamic processes of cavitation. First, the processes of growth and collapse are analysed, and the relationships between the hydraulic oil temperature and bubble growth and collapse are deduced. The effect of temperature is then considered on the hydraulic oil viscosity and saturated vapour pressure. Additionally, an improved form of the Rayleigh–Plesset equation is developed. The effect of cavitation on the hydraulic oil temperature is experimentally studied and the effects of cavitation bubble collapse in the hydraulic system are summarised. Using the cone-type throttle valve as an example, a method to suppress cavitation is proposed.展开更多
Inspired by the simple yet amazing morphology of the Octopus, we propose the design, fabrication, and characterization of multi-material bio-inspired soft Octopus robot (Octobot). 3D printed molds for tentacles and he...Inspired by the simple yet amazing morphology of the Octopus, we propose the design, fabrication, and characterization of multi-material bio-inspired soft Octopus robot (Octobot). 3D printed molds for tentacles and head were used. The tentacles of the Octobot were casted using Ecoflex-0030 while head was fabricated using relatively flexible material, i.e., OOMOO-25. The head is attached to the functionally responsive tentacles (each tentacle is of 79.12 mm length and 7 void space diameter), whereas Shape Memory Alloy (SMA) muscle wires of 0.5 mm thickness are used in Octobot tentacles for dual thrust generation and actuation of Octobot. The tentacles were separated in two groups and were synchronously actuated. Each tentacle of the developed Octobot contains a pair of SMA muscles (SMA-α and SMA-β). SMA-α muscles being the main actuator, was powered by 9 V, 350 mA power supply, whereas SMA-β was used to provide back thrust and thus helps to increase the actuation frequency. Simulation work of the proposed model was performed in the SolidWorks environment to verify the vertical velocity using the octopus tentacle actuation. The design morphology of Octobot was optimized using simulation and TRACKER software by analyzing the experimental data of angle, displacement, and velocity of real octopus. The as-developed Octobot can swim at variable frequencies (0.5–2 Hz) with the average speed of 25 mm/s (0.5 BLS). Therefore, the proposed soft Octopus robot showed an excellent capability of mimicking the gait pattern of its natural counterpart.展开更多
In recent years fluids containing suspension of nanometer sized particles have been an active area of research due to their enhanced thermo physical properties over the base fluids like water,oil etc.Nanofluids posses...In recent years fluids containing suspension of nanometer sized particles have been an active area of research due to their enhanced thermo physical properties over the base fluids like water,oil etc.Nanofluids possess immense potential applications to improve heat transfer and energy efficient in several areas including automobile,micro electronics,nuclear,space and power generation.Nowadays most of the researchers are trying to use the nanofluids in automobile for various applications such as coolant,fuel additives,lubricant,shock absorber and refrigerant.The goal of this paper is to create the awareness on the promise of nanofluids and the impact it will have on the future automotive industry.This paper also presents a comprehensive data of nanofluids application in automobile for various aspects.展开更多
文摘This study evaluates the Fuzzy Analytical Hierarchy Process(FAHP)as a multi-criteria decision(MCD)support tool for selecting appropriate additive manufacturing(AM)techniques that align with cleaner production and environmental sustainability.The FAHP model was validated using an example of the production of aircraft components(specifically fuselage)employing AM technologies such as Wire Arc Additive Manufacturing(WAAM),laser powder bed fusion(L-PBF),Binder Jetting(BJ),Selective Laser Sintering(SLS),and Laser Metal Deposition(LMD).The selection criteria prioritized eco-friendly manufacturing considerations,including the quality and properties of the final product(e.g.,surface finish,high strength,and corrosion resistance),service and functional requirements,weight reduction for improved energy efficiency(lightweight structures),and environmental responsibility.Sustainability metrics,such as cost-effectiveness,material efficiency,waste minimization,and environmental impact,are central to the evaluation process.A computer-aided modeling approach was also used to simulate the performance of aluminum(AA7075 T6),steel(304),and titanium alloy(Ti6Al4V)for fuselage development.The results demonstrate that MCD approaches such as FAHP can effectively guide the selection of AM technologies that meet functional and technical requirements while minimizing environmental degradation footprints.Furthermore,the aluminumalloy outperformed the other materials investigated in the simulation with the lowest stress concentration and least deformation.This study contributes to advancing cleaner production practices by providing a decision-making framework for sustainable and eco-friendly manufacturing,enabling manufacturers to adopt AM technologies that promote environmental responsibility and sustainable development,while maintaining product quality and performance.
文摘The Industrial Internet of Things(IIoT)has brought numerous benefits,such as improved efficiency,smart analytics,and increased automation.However,it also exposes connected devices,users,applications,and data generated to cyber security threats that need to be addressed.This work investigates hybrid cyber threats(HCTs),which are now working on an entirely new level with the increasingly adopted IIoT.This work focuses on emerging methods to model,detect,and defend against hybrid cyber attacks using machine learning(ML)techniques.Specifically,a novel ML-based HCT modelling and analysis framework was proposed,in which L1 regularisation and Random Forest were used to cluster features and analyse the importance and impact of each feature in both individual threats and HCTs.A grey relation analysis-based model was employed to construct the correlation between IIoT components and different threats.
基金supported by the Basic Science Research Program through the National Research Foundation of Korea(NRF)grant funded by the Korean government(MSIT)(2021R1A4A2000934).
文摘The metal-organic framework(MOF)derived Ni–Co–C–N composite alloys(NiCCZ)were“embedded”inside the carbon cloth(CC)strands as opposed to the popular idea of growing them upward to realize ultrastable energy storage and conversion application.The NiCCZ was then oxygen functionalized,facilitating the next step of stoichiometric sulfur anion diffusion during hydrothermal sulfurization,generating a flower-like metal hydroxysulfide structure(NiCCZOS)with strong partial implantation inside CC.Thus obtained NiCCZOS shows an excellent capacity when tested as a supercapacitor electrode in a three-electrode configuration.Moreover,when paired with the biomass-derived nitrogen-rich activated carbon,the asymmetric supercapacitor device shows almost 100%capacity retention even after 45,000 charge–discharge cycles with remarkable energy density(59.4 Wh kg^(-1)/263.8μWh cm^(–2))owing to a uniquely designed cathode.Furthermore,the same electrode performed as an excellent bifunctional water-splitting electrocatalyst with an overpotential of 271 mV for oxygen evolution reaction(OER)and 168.4 mV for hydrogen evolution reaction(HER)at 10 mA cm−2 current density along with 30 h of unhinged chronopotentiometric stability performance for both HER and OER.Hence,a unique metal chalcogenide composite electrode/substrate configuration has been proposed as a highly stable electrode material for flexible energy storage and conversion applications.
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.
文摘Innovative definitions of the electric and magnetic diffusivities through conducting mediums and innovative diffusion equations of the electric charges and magnetic flux are verified in this article. Such innovations depend on the analogy of the governing laws of diffusion of the thermal, electrical, and magnetic energies and newly defined natures of the electric charges and magnetic flux as energy, or as electromagnetic waves, that have electric and magnetic potentials. The introduced diffusion equations of the electric charges and magnetic flux involve Laplacian operator and the introduced diffusivities. Both equations are applied to determine the electric and magnetic fields in conductors as the heat diffusion equation which is applied to determine the thermal field in steady and unsteady heat diffusion conditions. The use of electric networks for experimental modeling of thermal networks represents sufficient proof of similarity of the diffusion equations of both fields. By analysis of the diffusion phenomena of the three considered modes of energy transfer;the rates of flow of these energies are found to be directly proportional to the gradient of their volumetric concentration, or density, and the proportionality constants in such relations are the diffusivity of each energy. Such analysis leads also to find proportionality relations between the potentials of such energies and their volumetric concentrations. Validity of the introduced diffusion equations is verified by correspondence their solutions to the measurement results of the electric and magnetic fields in microwave ovens.
文摘Precise and robust three-dimensional object detection(3DOD)presents a promising opportunity in the field of mobile robot(MR)navigation.Monocular 3DOD techniques typically involve extending existing twodimensional object detection(2DOD)frameworks to predict the three-dimensional bounding box(3DBB)of objects captured in 2D RGB images.However,these methods often require multiple images,making them less feasible for various real-time scenarios.To address these challenges,the emergence of agile convolutional neural networks(CNNs)capable of inferring depth froma single image opens a new avenue for investigation.The paper proposes a novel ELDENet network designed to produce cost-effective 3DBounding Box Estimation(3D-BBE)froma single image.This novel framework comprises the PP-LCNet as the encoder and a fast convolutional decoder.Additionally,this integration includes a Squeeze-Exploit(SE)module utilizing the Math Kernel Library for Deep Neural Networks(MKLDNN)optimizer to enhance convolutional efficiency and streamline model size during effective training.Meanwhile,the proposed multi-scale sub-pixel decoder generates high-quality depth maps while maintaining a compact structure.Furthermore,the generated depthmaps provide a clear perspective with distance details of objects in the environment.These depth insights are combined with 2DOD for precise evaluation of 3D Bounding Boxes(3DBB),facilitating scene understanding and optimal route planning for mobile robots.Based on the estimated object center of the 3DBB,the Deep Reinforcement Learning(DRL)-based obstacle avoidance strategy for MRs is developed.Experimental results demonstrate that our model achieves state-of-the-art performance across three datasets:NYU-V2,KITTI,and Cityscapes.Overall,this framework shows significant potential for adaptation in intelligent mechatronic systems,particularly in developing knowledge-driven systems for mobile robot navigation.
基金funded by National Science and Technology Council,Taiwan,grant numbers 112-2622-E-992-022 and 112-2221-E-992-086.
文摘The gantry crane system is a crucial equipment for loading and unloading containers at the shore site.The existing trend of crane technology is in the transition from in-site operators to remote operators outside the cargo handling site,which will comply with all safety regulations,including conditional crane monitoring.However,remote control introduces certain drawbacks in machine maintenance,as no on-site operators can provide real-time feedback on abnormalities.Therefore,this study proposes a failure detection system that uses vibratory sensors installed on machines to monitor and provide early warnings for various failures.For faulty event identification,the Fast Fourier Transform is carried out for the raw vibratory signals,and several frequency bands are classified by using t-SNE to evaluate the significance among clusters.The adjustment of hyperparameters of the t-SNE will alter the quality of the classification of different events,and this process is conventionally operated in accordance with users’experience.In this study,we propose a novel rating approach to automatically tune the hyperparameters of t-SNE to evaluate the separation and cluster compactness of the t-SNE results.Then,the results of clusters served as input features for training the faulty event detection model,and the detection model shows more than 95%accuracy in identifying different abnormal conditions of the main hosting motor.
文摘This paper presents the rigorous study of mobile robot navigation techniques used so far.The step by step investigations of classical and reactive approaches are made here to understand the development of path planning strategies in various environmental conditions and to identify research gap.The classical approaches such as cell decomposition(CD),roadmap approach(RA),artificial potential field(APF);reactive approaches such as genetic algorithm(GA),fuzzy logic(FL),neural network(NN),firefly algorithm(FA),particle swarm optimization(PSO),ant colony optimization(ACO),bacterial foraging optimization(BFO),artificial bee colony(ABC),cuckoo search(CS),shuffled frog leaping algorithm(SFLA)and other miscellaneous algorithms(OMA)are considered for study.The navigation over static and dynamic condition is analyzed(for single and multiple robot systems)and it has been observed that the reactive approaches are more robust and perform well in all terrain when compared to classical approaches.It is also observed that the reactive approaches are used to improve the performance of the classical approaches as a hybrid algorithm.Hence,reactive approaches are more popular and widely used for path planning of mobile robot.The paper concludes with tabular data and charts comparing the frequency of individual navigational strategies which can be used for specific application in robotics.
基金Project supported by Research Funds from Chosun University(2009),Korea
文摘Thermal deformation of aluminum alloy casting materials for manufacturing the tire mold was numerically investigated.The AC7A and AC4C casting material was selected as casting material and the metal casting device was used in order to manufacture the mold product of automobile tire in the actual industrial field.The temperature distribution and the cooling time of casting materials were numerically calculated by finite element analysis (FEA).Also,the thermal deformation such as displacement and stress distribution was calculated from the temperature results.The thermal deformation was closely related to the temperature difference between the surface and inside of the casting.The numerical analysis results reveal that the thermal deformation of AC7A casting material is higher than that of AC4C casting material.Also,the thermal deformation results at the central part are larger than that on the side of casting because of the shrinkage caused by the cooling speed difference.
基金funded by the Thailand Research Fund(RTA6180010).
文摘Horizontal axis wind turbines are some of the most widely used clean energy generators in the world.Horizontal axis wind turbine blades need to be designed for optimization in order to maximize efficiency and simultaneously minimize the cost of energy.This work presents the optimization of new MEXICO blades for a horizontal axis wind turbine at the wind speed of 10 m/s.The optimization problem is posed to maximize the power coefficient while the design variables are twist angles on the blade radius and rotating axis positions on a chord length of the airfoils.Computational fluid dynamics was used for the aerodynamic simulation.Surrogate-assisted optimization was applied to reduce computational time.A surrogate model called a Kriging model,using a Gaussian correlation function along with various regression models,was applied while a genetic algorithm was used as an optimizer.The results obtained in this study are discussed and compared with those obtained from the original model.It was found that the Kriging model with linear regression gives better results than the Kriging model with second-order polynomial regression.The optimum blade obtained in this study showed better performance than the original blade at a low wind speed of 10 m/s.
文摘This paper surveys the recent advances on the modeling and control of hysteresis of piezoelectric actuators(PTAs)in the context of high precision applications of atomic force microscopes(AFMs).The current states,findings,and outcomes on hysteresis modeling and control in terms of achievable bandwidth and accuracy are discussed in detailed.Future challenges and the scope of possible research are presented to pave the way to video rate atomic force microscopy.
基金Naval Research Board, DRDO, Govt. of INDIA, vide funded projectRef. no. DNRD/05/4003/NRB/85 dt 30.10.2006 for sponsoring FSW machine
文摘Friction stir welding（FSW） is a solid state joining technique developed to join high strength aluminum alloys and various ceramic reinforced metal matrix composites（MMCs）.FSW produces sound welds in MMCs without any deleterious reaction between reinforcement and matrix.The present work focused on the effect of FSW parameters on the tensile strength of Al-B4C composite joints.The central composite design of four factors and five levels was used to control the number of experiments.A mathematical model was developed to analyze the influence of FSW parameters.The results indicated that the joint fabricated using rotational speed of 1000 r/min,welding speed of 1.3 mm/s,axial force of 10 kN and the reinforcement of 12% showed larger tensile strength compared with the other joints.The developed model was optimized to maximize the tensile strength using generalized reduced gradient method.The metallographic analysis of the joints showed the presence of various zones such as weld nugget（WN） zone,thermo mechanically affected zone（TMAZ） and heat affected zone（HAZ）.The substantial grain refinement of aluminum matrix as well as significant size reduction of B4C particles was observed in the weld nugget.TMAZ was plastically deformed,thermally affected and exhibited elongated aluminum grains.
文摘In order to provide data for joints control of our recently designed crucian hke biomlmetlc robot fish, an A-ray photograph technology was adopted to determine the number and length of vertebral joints. A frame-by-frame analysis of high-speed videotapes was conducted to quantify the kinematics of crucian at four speeds （12.651 cm·s^-1, 18.201 cm·s^-1, 21.901 cm·s^-1, 24.368cm·s^-1） during cruising. In addition to a brief introduction to experimental conditions and methods, we analyzed the influence of individual diversity on the absolute length as well as the non-dimensional length of vertebral joints. We also presented the maximal angular velocity and acceleration of vertebral joints under four swimming speeds, and provided the change of relative rotation angle, angular difference, angular velocity and angular acceleration of the rear vertebral joints with time at a certain swimming speed of 12.651 cm·s^-1. At last, we presented the maximal lateral displacement of each mark at that speed. The study found that the influence of individual diversity on the non-dimensional length of vertebral joints is not significant; the maximal angular velocity and acceleration of vertebral joints increase with swimming speed; angular difference, angular velocity and angular acceleration exhibit two maximal values over one period at a certain swimming speed.
文摘This paper reports the effect of friction stir welding （FSW） process parameters on tensile strength of cast LM6 aluminium alloy. Joints were made by using different combinations of tool rotation speed, welding speed and axial force each at four levels. The quality of weld zone was investigated using macrostructure and microstructure analysis. Tensile strength of the joints were evaluated and correlated with the weld zone hardness and microstructure. The joint fabricated using a rotational speed of 900 r/min, a welding speed of 75 mm/min and an axial force of 3 kN showed superior tensile strength compared with other joints. The tensile strength and microhardness of the welded joints for the optimum conditions were 166 MPa and 64.8 Hv respectively.
文摘Nowadays,quadcopters are presented in many life applications which require the performance of automatic takeoff,trajectory tracking,and automatic landing.Thus,researchers are aiming to enhance the performance of these vehicles through low-cost sensing solutions and the design of executable and robust control techniques.Due to high nonlinearities,strong couplings and under-actuation,the control design process of a quadcopter is a rather challenging task.Therefore,the main objective of this work is demonstrated through two main aspects.The first is the design of an adaptive neuro-fuzzy inference system(ANFIS)controller to develop the attitude and altitude of a quadcopter.The second is to create a systematic framework for implementing flight controllers in embedded systems.A suitable model of the quadcopter is also developed by taking into account aerodynamics effects.To show the effectiveness of the ANFIS approach,the performance of a well-trained ANFIS controller is compared to a classical proportional-derivative(PD)controller and a properly tuned fuzzy logic controller.The controllers are compared and tested under several different flight conditions including the capability to reject external disturbances.In the first stage,performance evaluation takes place in a nonlinear simulation environment.Then,the ANFIS-based controllers alongside attitude and position estimators,and precision landing algorithms are implemented for executions in a real-time autopilot.In precision landing systems,an IR-camera is used to detect an IR-beacon on the ground for precise positioning.Several flight tests of a quadcopter are conducted for results validation.Both simulations and experiments demonstrated superior results for quadcopter stability in different flight scenarios.
基金Projects(51505289,51275123)supported by the National Natural Science Foundation of China
文摘Cavitation bubble collapse has a great influence on the temperature of hydraulic oil. Herein, cone-type throttle valve experiments are carried out to study the thermodynamic processes of cavitation. First, the processes of growth and collapse are analysed, and the relationships between the hydraulic oil temperature and bubble growth and collapse are deduced. The effect of temperature is then considered on the hydraulic oil viscosity and saturated vapour pressure. Additionally, an improved form of the Rayleigh–Plesset equation is developed. The effect of cavitation on the hydraulic oil temperature is experimentally studied and the effects of cavitation bubble collapse in the hydraulic system are summarised. Using the cone-type throttle valve as an example, a method to suppress cavitation is proposed.
基金This work was supported by the National Research Foundation of Korea(NRF)Grant funded by the Korea government(MSIT)(NRF-2022R1A2C2004771)Internal Research Grant by ORIC,SukkurIBA University 2022.
文摘Inspired by the simple yet amazing morphology of the Octopus, we propose the design, fabrication, and characterization of multi-material bio-inspired soft Octopus robot (Octobot). 3D printed molds for tentacles and head were used. The tentacles of the Octobot were casted using Ecoflex-0030 while head was fabricated using relatively flexible material, i.e., OOMOO-25. The head is attached to the functionally responsive tentacles (each tentacle is of 79.12 mm length and 7 void space diameter), whereas Shape Memory Alloy (SMA) muscle wires of 0.5 mm thickness are used in Octobot tentacles for dual thrust generation and actuation of Octobot. The tentacles were separated in two groups and were synchronously actuated. Each tentacle of the developed Octobot contains a pair of SMA muscles (SMA-α and SMA-β). SMA-α muscles being the main actuator, was powered by 9 V, 350 mA power supply, whereas SMA-β was used to provide back thrust and thus helps to increase the actuation frequency. Simulation work of the proposed model was performed in the SolidWorks environment to verify the vertical velocity using the octopus tentacle actuation. The design morphology of Octobot was optimized using simulation and TRACKER software by analyzing the experimental data of angle, displacement, and velocity of real octopus. The as-developed Octobot can swim at variable frequencies (0.5–2 Hz) with the average speed of 25 mm/s (0.5 BLS). Therefore, the proposed soft Octopus robot showed an excellent capability of mimicking the gait pattern of its natural counterpart.
文摘In recent years fluids containing suspension of nanometer sized particles have been an active area of research due to their enhanced thermo physical properties over the base fluids like water,oil etc.Nanofluids possess immense potential applications to improve heat transfer and energy efficient in several areas including automobile,micro electronics,nuclear,space and power generation.Nowadays most of the researchers are trying to use the nanofluids in automobile for various applications such as coolant,fuel additives,lubricant,shock absorber and refrigerant.The goal of this paper is to create the awareness on the promise of nanofluids and the impact it will have on the future automotive industry.This paper also presents a comprehensive data of nanofluids application in automobile for various aspects.
