Autonomous driving technology is constantly developing to a higher level of complex scenes,and there is a growing demand for the utilization of end-to-end data-driven control.However,the end-to-end path tracking proce...Autonomous driving technology is constantly developing to a higher level of complex scenes,and there is a growing demand for the utilization of end-to-end data-driven control.However,the end-to-end path tracking process often encounters challenges in learning efficiency and generalization.To address this issue,this paper designs a deep deterministic policy gradient(DDPG)-based reinforcement learning strategy that integrates imitation learning and feedforward exploration in the path following process.In imitation learning,the path tracking control data generated by the model predictive control(MPC)method is used to train an end-to-end steering control model of a deep neural network.Another feedforward exploration behavior is predicted by road curvature and vehicle speed,and adds it and imitation learning to the DDPG reinforcement learning to obtain decision-making experience and action prediction behavior of the path tracking process.In the reinforcement learning process,imitation learning is used to update the pre-training parameters of the actor network,and a feedforward steering technique with random noise is adopted for strategy exploration.In the reward function,a hierarchical progressive reward form and a constrained objective reward function referring to MPC are designed,and the actor-critic network architecture is determined.Finally,the path tracking performance of the designed method is verified by comparing various training results,simulations,and HIL tests.The results show that the designed method can effectively utilize pre-training and feedforward prior experience to obtain optimal path tracking performance of an autonomous vehicle,and has better generalization ability than other methods.This study provides an efficient control scheme for improving the end-to-end control performance of autonomous vehicles.展开更多
To address the issue of scarce labeled samples and operational condition variations that degrade the accuracy of fault diagnosis models in variable-condition gearbox fault diagnosis,this paper proposes a semi-supervis...To address the issue of scarce labeled samples and operational condition variations that degrade the accuracy of fault diagnosis models in variable-condition gearbox fault diagnosis,this paper proposes a semi-supervised masked contrastive learning and domain adaptation(SSMCL-DA)method for gearbox fault diagnosis under variable conditions.Initially,during the unsupervised pre-training phase,a dual signal augmentation strategy is devised,which simultaneously applies random masking in the time domain and random scaling in the frequency domain to unlabeled samples,thereby constructing more challenging positive sample pairs to guide the encoder in learning intrinsic features robust to condition variations.Subsequently,a ConvNeXt-Transformer hybrid architecture is employed,integrating the superior local detail modeling capacity of ConvNeXt with the robust global perception capability of Transformer to enhance feature extraction in complex scenarios.Thereafter,a contrastive learning model is constructed with the optimization objective of maximizing feature similarity across different masked instances of the same sample,enabling the extraction of consistent features from multiple masked perspectives and reducing reliance on labeled data.In the final supervised fine-tuning phase,a multi-scale attention mechanism is incorporated for feature rectification,and a domain adaptation module combining Local Maximum Mean Discrepancy(LMMD)with adversarial learning is proposed.This module embodies a dual mechanism:LMMD facilitates fine-grained class-conditional alignment,compelling features of identical fault classes to converge across varying conditions,while the domain discriminator utilizes adversarial training to guide the feature extractor toward learning domain-invariant features.Working in concert,they markedly diminish feature distribution discrepancies induced by changes in load,rotational speed,and other factors,thereby boosting the model’s adaptability to cross-condition scenarios.Experimental evaluations on the WT planetary gearbox dataset and the Case Western Reserve University(CWRU)bearing dataset demonstrate that the SSMCL-DA model effectively identifies multiple fault classes in gearboxes,with diagnostic performance substantially surpassing that of conventional methods.Under cross-condition scenarios,the model attains fault diagnosis accuracies of 99.21%for the WT planetary gearbox and 99.86%for the bearings,respectively.Furthermore,the model exhibits stable generalization capability in cross-device settings.展开更多
The effect of La addition(0-0.30 wt%)on the microstructure and hardness of rheological squeeze casting brass alloys was experimentally investigated.The rheological squeeze casting process is improved by controlling th...The effect of La addition(0-0.30 wt%)on the microstructure and hardness of rheological squeeze casting brass alloys was experimentally investigated.The rheological squeeze casting process is improved by controlling the wall surface crystals and melt flow rate to realise the preparation of semi-solid melt with flow,and a brass alloy workpiece with La is produced.The microstructure and properties of the brass alloy samples were investigated using metallography,scanning electron microscopy,energy-dispersive X-ray spectroscopy,X-ray diffraction and hardness testing.The results indicate that the hardness of the rheological squeeze casting brass alloy is increased by 20.4%from 108 to 130 HBW with an increase in the La content from 0 to 0.30 wt%.The micro structural analysis results show that La significantly refines the primary a-phase grains,and the main mechanism is the constitutional undercooling and heterogeneous nucleation caused by the La enrichment in the front of the solid-liquid interface.The squeeze pressure promotes undercooling,which improves the nucleation rate and affects the solute diffusion and nucleus growth.The dual effects of these two aspects aggravate the grain refinement process,consequently increasing the number of grain boundaries and improving the hardness of the brass alloy.展开更多
A method for gearbox fault diagnosis consists of feature extraction andfault identification. Many methods for feature extraction have beendevised for exposing nature of vibration data of a defective gearbox. Inadditio...A method for gearbox fault diagnosis consists of feature extraction andfault identification. Many methods for feature extraction have beendevised for exposing nature of vibration data of a defective gearbox. Inaddition, features extracted from gearbox vibration data are identifiedby various classifiers. However, existing literatures leave much to bedesired in assessing performance of different combinatorial methods forgearbox fault diagnosis. To this end, this paper evaluated performance ofseveral typical combinatorial methods for gearbox fault diagnosis byassociating each of multifractal detrended fluctuation analysis (MFDFA),empirical mode decomposition (EMD) and wavelet transform (WT) witheach of neural network (NN), Mahalanobis distance decision rules(MDDR) and support vector machine (SVM). Following this,performance of different combinatorial methods was compared using agroup of gearbox vibration data containing slightly different faultpatterns. The results indicate that MFDFA performs better in featureextraction of gearbox vibration data and SVM does the same in faultidentification. Naturally, the method associating MFDFA with SVMshows huge potential for fault diagnosis of gearboxes. As a result, thispaper can provide some useful information on construction of a methodfor gearbox fault diagnosis.展开更多
In order to study the influence of thermal deformation of long-span cable- stayed bridge (LSCSB) on the dynamic characteristics of metro vehicle on the bridge, based on the theory of vehicle-track coupled dynamic...In order to study the influence of thermal deformation of long-span cable- stayed bridge (LSCSB) on the dynamic characteristics of metro vehicle on the bridge, based on the theory of vehicle-track coupled dynamics, the rigid-flexible coupled dynamic model of metro vehicle-track-LSCSB system is established by using finite element method and multi-rigid-body dynamics. Adopting this model, the deformation of LSCSB subject to temperature is analyzed, then the comprehensive effect of track random irregularity and rail deformation caused by temperature load is considered to study the dynamic characteristics of metro vehicle running through the bridge, and finally the influences of temperature increment and running speed on concerned dynamic indices of vehicle are studied. The results show that the LSCSB deforms obviously subject to temperature load, and the overall performance is that the cooling is arched, and the heating is bent, and the shape variable changes almost linearly with the temperature load. According to the parameters studied in this paper, the rail deformation caused by temperature load increases the wheel-rail vertical force, derailment coefficient and wheel load reduction rate by 1.5%, 3.1% and 5% respectively. The vertical acceleration of the vehicle body decreases by 2.4% under the cooling condition, while increases by 3.7% under the heating condition. The dynamic response of the bridge changes under temperature load. The maximum vertical and horizontal displacement in the middle of the main beam span are 6.24 mm and 2.19 mm respectively, and the maximum vertical and horizontal acceleration are 1.29 cm/s<sup>2</sup> and 2.54cm/s<sup>2</sup> respectively. The derailment coefficient and vertical acceleration of vehicle body are more affected by temperature load, and the wheel load reduction rate and wheel-rail vertical force are more affected by speed. The conclusion of this paper provides a reference for subsequent scholars to study the influence of thermal deformation on the dynamic response of vehicles on LSCSB.展开更多
The flexible resonance phenomenon of a carbody greatly affects the stability and safety of high-speed trains.Therefore,an accurate finite element(FE)model is crucial for establishing a rigid-flexible multi-body dynami...The flexible resonance phenomenon of a carbody greatly affects the stability and safety of high-speed trains.Therefore,an accurate finite element(FE)model is crucial for establishing a rigid-flexible multi-body dynamics model and revealing the flexible resonance mechanism of high-speed trains.In this paper,we introduced an effective calibration and validation methodology for a carbody FE model of high-speed trains based on experimental modal analysis(EMA).A detailed three-dimensional(3D)carbody FE model that considered practical constraints was developed,and the carbody material parameters were optimized using a genetic algorithm(GA).Based on the updated model,a high-speed railway vehicle-track rigid-flexible coupled dynamics model was established.Results showed excellent agreement between the numerical simulations and field measurements.The proposed method was able to accurately reproduce the carbody flexible resonance phenomenon and elastic modal frequency observed on site.展开更多
The research on rolling bearing early fault detection is mainly focused on degradation index extraction and adaptive setting of alarm threshold.The mainstream methods are to extract degradation indicators based on ada...The research on rolling bearing early fault detection is mainly focused on degradation index extraction and adaptive setting of alarm threshold.The mainstream methods are to extract degradation indicators based on adaptive features and set adaptive alarm thresholds based on the Shewhart control chart.However,the adaptive feature extraction method does not consider the correlation between features,and the Shewhart control chart is not sensitive to small fluctuations caused by early faults.In this study,a rolling bearing early fault detection method based on a feature clustering fusion degradation index is proposed.The multidomain statistical features are extracted to form the initial feature set,and the improved hierarchical clustering algorithm is combined with the feature evaluation index to select features to form a preferred feature subset,to ensure the richness of index information and reduce redundancy.After the construction of the degradation index,to suppress the interference caused by nonstationary and abnormal shocks in early fault detection,the accurate evaluation method and anomaly determination strategy of control chart parameters are studied,and an improved exponential weighted move average control chart is designed to monitor the degradation index.The effectiveness and superiority of the proposed method are verified by public data sets.This research provides a rolling bearing early fault detection method,which can provide comprehensive degradation indicators,eliminate interference caused by random anomalies and running in periods,and achieve an accurate detection of early bearing failures.展开更多
Soft pneumatic structures are promising for the actuation of soft machines,and substantial advances have occurred in their innovative design and functional verification.However,most pneumatic structures lack self-sens...Soft pneumatic structures are promising for the actuation of soft machines,and substantial advances have occurred in their innovative design and functional verification.However,most pneumatic structures lack self-sensing abilities,resulting in a lack of motion state feedback and difficulty in achieving real-time closed-loop control.Herein,a soft pneumatic composite structure(SPCS)with integrated actuation and sensing abilities is developed by combining a bellows-shaped magnetic elastomer and a wire structure.The SPCS can generate an induced voltage under deformation.The SPCS mechanical and magnetoelectric characteristics are studied comprehensively.The SPCS experimental maximum contraction is 27 mm,which is close to the theoretical and numerical results.When the SPCS is actuated by a pressure of-40 kPa,it will generate a peak induced voltage of 1.01 mV.With the increase in magnetic powder content and turns of the spiral wire,the induced voltage also increases.Additionally,two SPCSs are used to develop a self-sensing actuator,which can accurately perceive the bending direction and recognize the magnitude and direction of external force.A self-sensing soft gripper is developed,which can sense the grasping status and predict the width of grasped objects.Furthermore,a smart vehicle detection system composed of two SPCSs is proposed,which can detect the number,speed,and weight of passing vehicles.Consequently,the SPCS has numerous potential applications in soft sensors and self-sensing intelligent soft machines.展开更多
Under sustained strong stochastic impact loads,floating-supported friction plates are susceptible to the formation of fatigue cracks that propagate along the rim.The nonlinearity and randomness introduced by the crack...Under sustained strong stochastic impact loads,floating-supported friction plates are susceptible to the formation of fatigue cracks that propagate along the rim.The nonlinearity and randomness introduced by the cracked teeth participating in the impacts significantly influence the service life and reliability of the transmission system.In this paper,an improved stiffness excitation modeling method is developed for friction plate teeth with rim cracks.It overcomes the limitations of traditional approaches that fail to accurately assess the narrow-band,large-diameter friction plate teeth with rim cracks due to constraints imposed by boundary conditions.Then,an original dynamic impact model for the floating-supported friction plate and inner hub system is proposed,incorporating the effects of bending-torsional-axial-tilting coupled motions on tooth mesh excitations and dynamic responses.This model addresses the limitations of conventional models that only consider bending-torsion coupling,thereby providing a more comprehensive representation of the system's multi-dimensional dynamic behavior.The effects of the crack propagation depth and the number of cracked teeth on the stochastic impact characteristics and vibration responses of the system are investigated.Furthermore,finite element simulations and experimental tests are conducted to validate the cracked tooth stiffness excitations and dynamic impact responses,respectively.The proposed model is anticipated to provide both a theoretical foundation and practical guidance for fault diagnosis and reliability assessment of clutch friction plates.展开更多
Penicillium expansum infection is a primary cause of postharvest deterioration in apples,impacting their quality and processed products,leading to economic losses and health risks.This study aimed to investigate quali...Penicillium expansum infection is a primary cause of postharvest deterioration in apples,impacting their quality and processed products,leading to economic losses and health risks.This study aimed to investigate quality changes in‘Fuji’apples during postharvest disease progression and to assess optical properties as potential monitoring tools.The absorption coefficient(μa)and reduced scattering coefficient(μs’)of healthy and infected apples were measured within the 600-1050 nm wavelength range using a single integrating sphere(SIS)system.Additionally,liquid chromatography and scanning electron microscopy(SEM)were used to evaluate physicochemical properties and microstructural characteristics of apple flesh as indicators of quality changes in infected tissue.After 12 days of storage,the soluble solids content(SSC)of infected apples decreased from 14%to 9%,and moisture content(MC)initially decreased from 83%to 59%before rising to 85%.Total soluble sugar content declined from 119 g kg^(-1)-78 g kg^(-1).Infected apples exhibited higher MC,lower soluble sugars,and lower SSC compared to healthy ones.Theμa value significantly increased,reaching twice that of healthy flesh by day 12,while theμs’value decreased to 0.29 mm⁻1.Correlation analysis revealed strong associations between SSC,MC,and soluble sugars with optical properties,with a maximum correlation of 0.966.Path coefficient analysis indicated that MC was the primary factor affecting changes in μa andμs’during infection.This study underscores the potential of optical properties as indicators of physicochemical and microstructural changes in apples during pathogen infection.展开更多
Ceramics are extensively used in protective structures which are often subjected to projectile impacts.During an impact process of a ceramic target by a projectile,fragmentation occurs in both the target and the proje...Ceramics are extensively used in protective structures which are often subjected to projectile impacts.During an impact process of a ceramic target by a projectile,fragmentation occurs in both the target and the projectile.It is challenging to simulate such events and predict residual mass and velocity of the projectile.In this work,we attempt to use smoothed particle hydrodynamics(SPH)in LS-DYNA to reproduce fragmentation of the target and the projectile and predict residual mass and velocity of the projectile during a projectile impact of a ceramic target.SPH models for an alumina ceramic tile impacted by a blunt tungsten heavy alloy projectile are established.SPH simulation results of residual mass and velocity of the projectile as well as ejecta and bulge movements of the ceramic tile are obtained and compared with experimental data and simulation results of other numerical approaches.It is found that SPH simulation can properly reproduce the impact fragmentation of the target and the projectile,and shows advantages over existing numerical approaches in the prediction accuracy of residual mass and velocity.Moreover,effects of some numerical aspects of SPH,including particle spacing,contact treatment and parameters in artificial viscosity and smoothing length,on simulation results are identified.A simple approach using identical smoothing length and balanced artificial viscosity is proposed to reduce particle spacing sensitivity.The observed parametric effects and the proposed approach will provide guidance to set appropriate parameters values for SPH simulation of impact fragmentation.展开更多
Prosthesis implantation and fat transplantation are common breast reconstructionmethods.In general,prosthesis implantation alone does not achieve a realistic enough appearance,and fat transplantation alone is difficul...Prosthesis implantation and fat transplantation are common breast reconstructionmethods.In general,prosthesis implantation alone does not achieve a realistic enough appearance,and fat transplantation alone is difficult to achieve in the correct capacity.To date,no reports have focused on methods of combining fat with implanted prostheses for breast reconstruction.Using a newly designed bionic ink(i.e.,polyether F127 diacrylate(F127DA)&poly(ethylene glycol)diacrylate(PEGDA))and projection-based three-dimensional bioprinting(PBP),we report the development of a new method for printing porous prostheses.PEGDA was used to improve the printing precision of the prosthesis by increasing the gel point of F127DA and reducing the impact of external temperature.The compression modulus of the printed prosthesis was very close to that of prostheses currently used in clinical practice and to that of natural breasts.Finally,stromal vascular fraction gel(SVF-gel),a human fat extract,was injected into the pores of the synthesized prostheses to prepare a prosthesis mixed with adipose tissue.These were implanted subcutaneously in nude mice to observe their biological performance.After 14 and 28 days of observation,the prosthesis showed good biocompatibility,and adipose tissues grew well in and around the prosthesis.This result shows that a porous prosthesis containing pre-placed adipose tissues is a promising breast reconstruction material.展开更多
Wind turbine is a key device to realize the utilization of wind energy,and it has been highly valued by all countries.But the mechanical gear transmission of the existing wind power device has the disadvantages of hig...Wind turbine is a key device to realize the utilization of wind energy,and it has been highly valued by all countries.But the mechanical gear transmission of the existing wind power device has the disadvantages of high vibration and noise,high failure rate,and short service time.Magneticfield modulation electromagnetic gear transmission is a new non-contact transmission method.However,the conventional modulation magnetic gear has low torque density and torque defects with largefluctuations.In order to overcome the gear transmis-sion problems of the existing semi-direct drive wind power generation machinery and improve the electromag-netic performance of the traditional magnetic gear transmission,this paper proposes a new transmission scheme of a non-contact semi-direct drive wind generator with a surface mount Halbach array modulated mag-netic gear method,and considers the electromagnetic properties of the semi-direct drive modulation magnetic gear of the wind turbine.Thefinite element software is used to construct the model of the surface-mounted Halbach array magnetic gear and the conventional gear,analyzed the distribution of magneticfield lines of the two magnetic gears,calculated the air gap magneticflux density of the inner and outer air gap,and obtained the main harmonics of the inner and outer air gap magnetic density;calculated the static torque and steady-state operating torque of the inner and outer rotors in the model,compared the air gapflux density,harmonics and torque of the magnetic gears.The simulation results show that the magneticfield modulation type mag-netic gear of the surface mount Halbach array magnetic gear method improves the magnetic induction wave-form of the inner and outer air gap,reduces the pulse torquefluctuation,and has a 60%higher static torque.Applying it to semi-direct drive wind power generation equipment not only overcomes the shortcomings of mechanical gears,but also has higher electromagnetic performance.Therefore,the surface-mounted Halbach array modulated magnetic gear can be used to replace the mechanical gearbox in the semi-direct drive wind power generation equipment.展开更多
A new type of transportation vehicle,the flying car,is attracting increasing attention in the automotive and aviation industries to meet people’s personalized transportation needs for urban air traffic and future tra...A new type of transportation vehicle,the flying car,is attracting increasing attention in the automotive and aviation industries to meet people’s personalized transportation needs for urban air traffic and future travel.With its vertical take-off and landing capability,flying cars can expand its feasible routes into 3D space.The above process,however,requires sufficient path planning to obtain optimal 3D path.To solve the above issue,the inspiration was drawn from animals in the natural world to design a type of flying car that can travel in various urban environments such as land and low altitude by using different components like wheels and propellers.Incorporating the motion characteristics of flying cars in the future urban environment,segmenting the energy consumption and time models of various stages of flying cars is conducted.The introduction of temporal A*algorithm into the new field of flying cars for the first time,the priority planning algorithm for multiple flying car groups based on an improved A*algorithm utilizing safety intervals is proposed.The proposed strategy is validated on different sizes of urban environment maps.The results indicate that on a complex map with 452 nodes,the strategy effectively reduces distance by 4.5 m,decreases energy consumption by 85.8%and improves planning speed.Compared with the strategy based on multi-commodity network flow integer linear programming,the planning results are roughly the same,but the weighted cost of employing this strategy is decreased by 5.2%,and the path distance is reduced by 0.34 m.展开更多
Dual fuel engine combustion characteristic using the mixture of compressed natural gas(NG) and ethanol as low reactivity fuel and diesel as high reactivity fuel was investigated experimentally in this work.Experiments...Dual fuel engine combustion characteristic using the mixture of compressed natural gas(NG) and ethanol as low reactivity fuel and diesel as high reactivity fuel was investigated experimentally in this work.Experiments were performed on an optical engine with double diesel injection strategy using the high-speed natural flame luminosity(NFL) imaging technique,and the flame temperature and soot volume fraction were extracted using the two-color method.NG was added into the ethanol/air mixture as an energy surplus and NG energy rate(NER) was set at 0%,50%,60% and 70%.The diesel pilot injection time(PIT) was set at-24℃A,-18℃A and-12℃A ATDC.Results indicate that adding surplus NG results in a delay in the ignition,growth in the combustion duration and pressure rise rate,an increase of in-cylinder pressure and indicated mean effective pressure(IMEP).Meanwhile,the addition of NG has significant effect on the flame development and soot formation characteristics but their sensitivities to the NER are PIT dependent.At-12℃A ATDC case,the increase in NER results in a substantial decrease in spatially integrated natural luminosity(SINL),flame area(FA)and total soot KL factor(TKL) peaks and a backward shift in the curves of SINL,FA and TKL.But at advanced PIT cases,the SINL,FA and TKL curves obviously grow up as the NER increases.Besides,advancing the PIT results in a longer ignition delay,shorter combustion duration and lower IMEP.Moreover,with advancing the PIT,the TKL peak and time integrated total soot KL factor(IKL) show the tendency of decrease for diesel-ethanol dual fuel.However,for diesel-ethanol-NG ternary fuel,the TKL peak and IKL first increase and then decrease.展开更多
Aiming at the problems of traditional centralized cloud computing which occupies large computing resources and creates high latency,this paper proposes a fault detection scheme for insulator self-explosion based on ed...Aiming at the problems of traditional centralized cloud computing which occupies large computing resources and creates high latency,this paper proposes a fault detection scheme for insulator self-explosion based on edge computing and DL(deep learning).In order to solve the high amount of computation brought by the deep neural network and meet the limited computing resources at the edge,a lightweight SSD(Single Shot MultiBox Detector)target recognition network is designed at the edge,which adopts the MobileNets network to replace VGG16 network in the original model to reduce redundant computing.In the cloud,three detection algorithms(Faster-RCNN,Retinanet,YOLOv3)with obvious differences in detection performance are selected to obtain the coordinates and confidence of the insulator self-explosion area,and then the self-explosion fault detection of the overhead transmission line is realized by a novel multimodel fusion algorithm.The experimental results show that the proposed scheme can effectively reduce the amount of uploaded data,and the average recognition accuracy of the cloud is 95.75%.In addition,it only increases the power consumption of edge devices by about 25.6W/h in their working state.Compared with the existing online monitoring technology of insulator selfexplosion at home and abroad,the proposed scheme has the advantages of low transmission delay,low communication cost and high diagnostic accuracy,which provides a new idea for online monitoring research of power internet of things equipment.展开更多
Background and objectives:Current technology of X-ray imaging can recognize hard foreign materials(FMs)such as metal and high-density plastic.However,low-density foreign bodies are still a challenge for food quality a...Background and objectives:Current technology of X-ray imaging can recognize hard foreign materials(FMs)such as metal and high-density plastic.However,low-density foreign bodies are still a challenge for food quality and safety assessment.Materials and methods:An electromagnetic vibration feeder aided by terahertz time-domain spectroscopy(THz-TDS)and imaging was inves-tigated for non-destructively detecting tea stalk and insect FMs mixed with tea leaves.Results:THz time-domain signals were employed directly to develop the K-nearest neighbor model with a precision of 100%,accuracy of 95.6%and recall of 98.7%in predicting the unknown samples.High contrast THz-TDS images were obtained by the separation method for the samples using electromagnetic vibration feeder.The characteristic parameters of the ratio of maximum length(L)to maximum width(W)and hue extracted from THz-TDS images indicated significant difference between tea leaves and FMs.Conclusions:The results suggested that electromagnetic vibration feeder combination with THz-TDS was feasible for detecting FMs in fin-ishingteaproducts.展开更多
Copper sulfide(Cu_(x)S)as a plasmonic solar photothermal semiconductor material that expands the light collection range by altering localized surface plasmon resonance(LSPR)to the near-to mid-infrared(IR)spectral regi...Copper sulfide(Cu_(x)S)as a plasmonic solar photothermal semiconductor material that expands the light collection range by altering localized surface plasmon resonance(LSPR)to the near-to mid-infrared(IR)spectral region.The versatile synthesis strategies of Cu_(x)S nanostructure offer its variability of morphology and provide additional freedom in tuning the optical property.Particularly,nanocage(or nanoshell)has hybridized plasmon resonances as a result of super-positioned nanosphere and nanocavity,which extends its receiving range of solar spectrum and increases light-to-heat conversion rate.Here,we offer novel“nanoink”and“nanofilm”developed from colloidal Cu_(27)S_(24)nanocages with excellent solar photothermal response.Via combining experimental measurement and theoretical calculation,we estimated the optical properties of covellite Cu_(27)S_(24).And based on obtained dielectric functions,we then calculated its solar photothermal performance,which was further validated by our experimental measurement.The simulation results showed that hollow Cu_(27)S_(24)nanocages have excellent solar photothermal performance,and exhibit much higher solar photothermal conversion efficiency than solid Cu_(27)S_(24)nanospheres.展开更多
In order to improve the poor discharge problem that may be caused by the unreasonable power distribution relationship of the battery pack in hybrid vehicles due to the improvement of fuel economy,this paper carries ou...In order to improve the poor discharge problem that may be caused by the unreasonable power distribution relationship of the battery pack in hybrid vehicles due to the improvement of fuel economy,this paper carries out the research of energy management strategy based on multi-objective optimization for a parallel plug-in hybrid vehicle.The optimization objectives are the optimal fuel economy and the minimum temperature rise of the battery.A vehicle power system model is established to provide a simulation platform for the subsequent verification of the control strategy.A short-term operating condition prediction model is constructed based on the Markov process,ensuring the energy management strategy meets the power balance demand in the local time domain in the future.A multi-objective optimization algorithm is used to enhance the improvement of the traditional equivalent fuel consumption minimization strategy by means of the prediction of the operating conditions,and a real-time search for the optimization is employed by selecting the equivalent factor as the control variable.By selecting the equivalent factor as the control variable for real-time optimization,the optimal time-varying equivalent factor sequence based on multi-objective optimization is obtained,which improves the power distribution between the engine and the motor drive.The results show that the improved control strategy can well trade-off the engine fuel economy and battery temperature rise index,and has excellent battery SOC maintenance capability.While confirming the effectiveness of the strategy,it is verified that it has strong robustness and multi-case generalization capability.展开更多
This study employs friction stir welding(FSW)technology to achieve the butt welding of 2mm thick 1060 aluminum and T2 copper.The research investigates the macroscopic formation,tensile properties,microhardness,and ele...This study employs friction stir welding(FSW)technology to achieve the butt welding of 2mm thick 1060 aluminum and T2 copper.The research investigates the macroscopic formation,tensile properties,microhardness,and electrochemical corrosion behavior of the welded joints.The results indicate that the welded joints exhibit excellent formation,with a tensile strength reaching 84.76%of that of the 1060 aluminum material.Well-formed welded joints can be obtained by controlling the rotation speed and welding speed within a certain range.However,the rotation speed has a more significant impact on the microhardness in the weld zone.The corrosion potential of T2 copper is higher than that of 1060 aluminum,forming a macroscopic galvanic couple between the two materials.The corrosion potential of the welded joint falls between that of T2 copper and 1060 aluminum.展开更多
基金Supported by National Natural Science Foundation of China(Grant No.52405104)Jiangxi Provincial Natural Science Foundation(Grant Nos.20242BAB20249 and 20232BAB204041)Science and Technology Project of Department of Transportation of Jiangxi Province(Grant No.2025QN003).
文摘Autonomous driving technology is constantly developing to a higher level of complex scenes,and there is a growing demand for the utilization of end-to-end data-driven control.However,the end-to-end path tracking process often encounters challenges in learning efficiency and generalization.To address this issue,this paper designs a deep deterministic policy gradient(DDPG)-based reinforcement learning strategy that integrates imitation learning and feedforward exploration in the path following process.In imitation learning,the path tracking control data generated by the model predictive control(MPC)method is used to train an end-to-end steering control model of a deep neural network.Another feedforward exploration behavior is predicted by road curvature and vehicle speed,and adds it and imitation learning to the DDPG reinforcement learning to obtain decision-making experience and action prediction behavior of the path tracking process.In the reinforcement learning process,imitation learning is used to update the pre-training parameters of the actor network,and a feedforward steering technique with random noise is adopted for strategy exploration.In the reward function,a hierarchical progressive reward form and a constrained objective reward function referring to MPC are designed,and the actor-critic network architecture is determined.Finally,the path tracking performance of the designed method is verified by comparing various training results,simulations,and HIL tests.The results show that the designed method can effectively utilize pre-training and feedforward prior experience to obtain optimal path tracking performance of an autonomous vehicle,and has better generalization ability than other methods.This study provides an efficient control scheme for improving the end-to-end control performance of autonomous vehicles.
基金supported by the National Natural Science Foundation of China Funded Project(Project Name:Research on Robust Adaptive Allocation Mechanism of Human Machine Co-Driving System Based on NMS Features,Project Approval Number:52172381).
文摘To address the issue of scarce labeled samples and operational condition variations that degrade the accuracy of fault diagnosis models in variable-condition gearbox fault diagnosis,this paper proposes a semi-supervised masked contrastive learning and domain adaptation(SSMCL-DA)method for gearbox fault diagnosis under variable conditions.Initially,during the unsupervised pre-training phase,a dual signal augmentation strategy is devised,which simultaneously applies random masking in the time domain and random scaling in the frequency domain to unlabeled samples,thereby constructing more challenging positive sample pairs to guide the encoder in learning intrinsic features robust to condition variations.Subsequently,a ConvNeXt-Transformer hybrid architecture is employed,integrating the superior local detail modeling capacity of ConvNeXt with the robust global perception capability of Transformer to enhance feature extraction in complex scenarios.Thereafter,a contrastive learning model is constructed with the optimization objective of maximizing feature similarity across different masked instances of the same sample,enabling the extraction of consistent features from multiple masked perspectives and reducing reliance on labeled data.In the final supervised fine-tuning phase,a multi-scale attention mechanism is incorporated for feature rectification,and a domain adaptation module combining Local Maximum Mean Discrepancy(LMMD)with adversarial learning is proposed.This module embodies a dual mechanism:LMMD facilitates fine-grained class-conditional alignment,compelling features of identical fault classes to converge across varying conditions,while the domain discriminator utilizes adversarial training to guide the feature extractor toward learning domain-invariant features.Working in concert,they markedly diminish feature distribution discrepancies induced by changes in load,rotational speed,and other factors,thereby boosting the model’s adaptability to cross-condition scenarios.Experimental evaluations on the WT planetary gearbox dataset and the Case Western Reserve University(CWRU)bearing dataset demonstrate that the SSMCL-DA model effectively identifies multiple fault classes in gearboxes,with diagnostic performance substantially surpassing that of conventional methods.Under cross-condition scenarios,the model attains fault diagnosis accuracies of 99.21%for the WT planetary gearbox and 99.86%for the bearings,respectively.Furthermore,the model exhibits stable generalization capability in cross-device settings.
基金Project supported by the financial support of the Fundamental Research Funds for the Central Universities(2020YJS146)。
文摘The effect of La addition(0-0.30 wt%)on the microstructure and hardness of rheological squeeze casting brass alloys was experimentally investigated.The rheological squeeze casting process is improved by controlling the wall surface crystals and melt flow rate to realise the preparation of semi-solid melt with flow,and a brass alloy workpiece with La is produced.The microstructure and properties of the brass alloy samples were investigated using metallography,scanning electron microscopy,energy-dispersive X-ray spectroscopy,X-ray diffraction and hardness testing.The results indicate that the hardness of the rheological squeeze casting brass alloy is increased by 20.4%from 108 to 130 HBW with an increase in the La content from 0 to 0.30 wt%.The micro structural analysis results show that La significantly refines the primary a-phase grains,and the main mechanism is the constitutional undercooling and heterogeneous nucleation caused by the La enrichment in the front of the solid-liquid interface.The squeeze pressure promotes undercooling,which improves the nucleation rate and affects the solute diffusion and nucleus growth.The dual effects of these two aspects aggravate the grain refinement process,consequently increasing the number of grain boundaries and improving the hardness of the brass alloy.
基金supported by Shandong ProvincialNatural Science Foundation China (ZR2012EEL07).
文摘A method for gearbox fault diagnosis consists of feature extraction andfault identification. Many methods for feature extraction have beendevised for exposing nature of vibration data of a defective gearbox. Inaddition, features extracted from gearbox vibration data are identifiedby various classifiers. However, existing literatures leave much to bedesired in assessing performance of different combinatorial methods forgearbox fault diagnosis. To this end, this paper evaluated performance ofseveral typical combinatorial methods for gearbox fault diagnosis byassociating each of multifractal detrended fluctuation analysis (MFDFA),empirical mode decomposition (EMD) and wavelet transform (WT) witheach of neural network (NN), Mahalanobis distance decision rules(MDDR) and support vector machine (SVM). Following this,performance of different combinatorial methods was compared using agroup of gearbox vibration data containing slightly different faultpatterns. The results indicate that MFDFA performs better in featureextraction of gearbox vibration data and SVM does the same in faultidentification. Naturally, the method associating MFDFA with SVMshows huge potential for fault diagnosis of gearboxes. As a result, thispaper can provide some useful information on construction of a methodfor gearbox fault diagnosis.
文摘In order to study the influence of thermal deformation of long-span cable- stayed bridge (LSCSB) on the dynamic characteristics of metro vehicle on the bridge, based on the theory of vehicle-track coupled dynamics, the rigid-flexible coupled dynamic model of metro vehicle-track-LSCSB system is established by using finite element method and multi-rigid-body dynamics. Adopting this model, the deformation of LSCSB subject to temperature is analyzed, then the comprehensive effect of track random irregularity and rail deformation caused by temperature load is considered to study the dynamic characteristics of metro vehicle running through the bridge, and finally the influences of temperature increment and running speed on concerned dynamic indices of vehicle are studied. The results show that the LSCSB deforms obviously subject to temperature load, and the overall performance is that the cooling is arched, and the heating is bent, and the shape variable changes almost linearly with the temperature load. According to the parameters studied in this paper, the rail deformation caused by temperature load increases the wheel-rail vertical force, derailment coefficient and wheel load reduction rate by 1.5%, 3.1% and 5% respectively. The vertical acceleration of the vehicle body decreases by 2.4% under the cooling condition, while increases by 3.7% under the heating condition. The dynamic response of the bridge changes under temperature load. The maximum vertical and horizontal displacement in the middle of the main beam span are 6.24 mm and 2.19 mm respectively, and the maximum vertical and horizontal acceleration are 1.29 cm/s<sup>2</sup> and 2.54cm/s<sup>2</sup> respectively. The derailment coefficient and vertical acceleration of vehicle body are more affected by temperature load, and the wheel load reduction rate and wheel-rail vertical force are more affected by speed. The conclusion of this paper provides a reference for subsequent scholars to study the influence of thermal deformation on the dynamic response of vehicles on LSCSB.
基金supported by the State Key Laboratory of Rail Transit Vehicle System(No.RVL2508)China,the National Natural Science Foundation of China(Nos.52388102 and U2268210)the Key Science and Technology Projects of CRRC(No.2020CYB147),China.
文摘The flexible resonance phenomenon of a carbody greatly affects the stability and safety of high-speed trains.Therefore,an accurate finite element(FE)model is crucial for establishing a rigid-flexible multi-body dynamics model and revealing the flexible resonance mechanism of high-speed trains.In this paper,we introduced an effective calibration and validation methodology for a carbody FE model of high-speed trains based on experimental modal analysis(EMA).A detailed three-dimensional(3D)carbody FE model that considered practical constraints was developed,and the carbody material parameters were optimized using a genetic algorithm(GA).Based on the updated model,a high-speed railway vehicle-track rigid-flexible coupled dynamics model was established.Results showed excellent agreement between the numerical simulations and field measurements.The proposed method was able to accurately reproduce the carbody flexible resonance phenomenon and elastic modal frequency observed on site.
基金Supported by National Key Research and Development Program(Grant No.2023YFB4203402)National Natural Science Foundation of China(Grant No.52375042)+1 种基金Chongqing Technology Innovation and Application Development Project(Grant No.CSTB2022TIAD-KPX0078)Chongqing Transportation Technology Project(Grant No.CQJT-CZKJ2024-10).
文摘The research on rolling bearing early fault detection is mainly focused on degradation index extraction and adaptive setting of alarm threshold.The mainstream methods are to extract degradation indicators based on adaptive features and set adaptive alarm thresholds based on the Shewhart control chart.However,the adaptive feature extraction method does not consider the correlation between features,and the Shewhart control chart is not sensitive to small fluctuations caused by early faults.In this study,a rolling bearing early fault detection method based on a feature clustering fusion degradation index is proposed.The multidomain statistical features are extracted to form the initial feature set,and the improved hierarchical clustering algorithm is combined with the feature evaluation index to select features to form a preferred feature subset,to ensure the richness of index information and reduce redundancy.After the construction of the degradation index,to suppress the interference caused by nonstationary and abnormal shocks in early fault detection,the accurate evaluation method and anomaly determination strategy of control chart parameters are studied,and an improved exponential weighted move average control chart is designed to monitor the degradation index.The effectiveness and superiority of the proposed method are verified by public data sets.This research provides a rolling bearing early fault detection method,which can provide comprehensive degradation indicators,eliminate interference caused by random anomalies and running in periods,and achieve an accurate detection of early bearing failures.
基金supported by the National Natural Science Foundation of China(Grant No.52405267)the Jiangxi Provincial Natural Science Foundation(Grant Nos.20242BAB25257,20232BAB214050)+1 种基金the China Postdoctoral Science Foundation(Grant No.2024M760877)the Natural Science Foundation of Hunan Province(Grant No.2025JJ60369)。
文摘Soft pneumatic structures are promising for the actuation of soft machines,and substantial advances have occurred in their innovative design and functional verification.However,most pneumatic structures lack self-sensing abilities,resulting in a lack of motion state feedback and difficulty in achieving real-time closed-loop control.Herein,a soft pneumatic composite structure(SPCS)with integrated actuation and sensing abilities is developed by combining a bellows-shaped magnetic elastomer and a wire structure.The SPCS can generate an induced voltage under deformation.The SPCS mechanical and magnetoelectric characteristics are studied comprehensively.The SPCS experimental maximum contraction is 27 mm,which is close to the theoretical and numerical results.When the SPCS is actuated by a pressure of-40 kPa,it will generate a peak induced voltage of 1.01 mV.With the increase in magnetic powder content and turns of the spiral wire,the induced voltage also increases.Additionally,two SPCSs are used to develop a self-sensing actuator,which can accurately perceive the bending direction and recognize the magnitude and direction of external force.A self-sensing soft gripper is developed,which can sense the grasping status and predict the width of grasped objects.Furthermore,a smart vehicle detection system composed of two SPCSs is proposed,which can detect the number,speed,and weight of passing vehicles.Consequently,the SPCS has numerous potential applications in soft sensors and self-sensing intelligent soft machines.
基金supported by the National Natural Science Foundation of China(Grant Nos.52505101,52475087,52475089,52365010)the Early-Career Young Scientists and Technologists Project of Jiangxi Province(Grant No.20252BEJ730175)。
文摘Under sustained strong stochastic impact loads,floating-supported friction plates are susceptible to the formation of fatigue cracks that propagate along the rim.The nonlinearity and randomness introduced by the cracked teeth participating in the impacts significantly influence the service life and reliability of the transmission system.In this paper,an improved stiffness excitation modeling method is developed for friction plate teeth with rim cracks.It overcomes the limitations of traditional approaches that fail to accurately assess the narrow-band,large-diameter friction plate teeth with rim cracks due to constraints imposed by boundary conditions.Then,an original dynamic impact model for the floating-supported friction plate and inner hub system is proposed,incorporating the effects of bending-torsional-axial-tilting coupled motions on tooth mesh excitations and dynamic responses.This model addresses the limitations of conventional models that only consider bending-torsion coupling,thereby providing a more comprehensive representation of the system's multi-dimensional dynamic behavior.The effects of the crack propagation depth and the number of cracked teeth on the stochastic impact characteristics and vibration responses of the system are investigated.Furthermore,finite element simulations and experimental tests are conducted to validate the cracked tooth stiffness excitations and dynamic impact responses,respectively.The proposed model is anticipated to provide both a theoretical foundation and practical guidance for fault diagnosis and reliability assessment of clutch friction plates.
基金support provided by National Key Research and Development Program of China(No.2022YFD2001804,2023YFD2001301)State Key Laboratory of Intelligent Agricultural Power Equipment Opening Project(No.SKLIAPE 2024012).
文摘Penicillium expansum infection is a primary cause of postharvest deterioration in apples,impacting their quality and processed products,leading to economic losses and health risks.This study aimed to investigate quality changes in‘Fuji’apples during postharvest disease progression and to assess optical properties as potential monitoring tools.The absorption coefficient(μa)and reduced scattering coefficient(μs’)of healthy and infected apples were measured within the 600-1050 nm wavelength range using a single integrating sphere(SIS)system.Additionally,liquid chromatography and scanning electron microscopy(SEM)were used to evaluate physicochemical properties and microstructural characteristics of apple flesh as indicators of quality changes in infected tissue.After 12 days of storage,the soluble solids content(SSC)of infected apples decreased from 14%to 9%,and moisture content(MC)initially decreased from 83%to 59%before rising to 85%.Total soluble sugar content declined from 119 g kg^(-1)-78 g kg^(-1).Infected apples exhibited higher MC,lower soluble sugars,and lower SSC compared to healthy ones.Theμa value significantly increased,reaching twice that of healthy flesh by day 12,while theμs’value decreased to 0.29 mm⁻1.Correlation analysis revealed strong associations between SSC,MC,and soluble sugars with optical properties,with a maximum correlation of 0.966.Path coefficient analysis indicated that MC was the primary factor affecting changes in μa andμs’during infection.This study underscores the potential of optical properties as indicators of physicochemical and microstructural changes in apples during pathogen infection.
基金National Natural Science Foundation of China(Grant No.11862005)Natural Science Foundation of Jiangxi Province of China(Grant No.20181BAB211012)Tianjin Natural Science Foundation of China(Grant No.18JCYBJC88500)is gratefully acknowledged.
文摘Ceramics are extensively used in protective structures which are often subjected to projectile impacts.During an impact process of a ceramic target by a projectile,fragmentation occurs in both the target and the projectile.It is challenging to simulate such events and predict residual mass and velocity of the projectile.In this work,we attempt to use smoothed particle hydrodynamics(SPH)in LS-DYNA to reproduce fragmentation of the target and the projectile and predict residual mass and velocity of the projectile during a projectile impact of a ceramic target.SPH models for an alumina ceramic tile impacted by a blunt tungsten heavy alloy projectile are established.SPH simulation results of residual mass and velocity of the projectile as well as ejecta and bulge movements of the ceramic tile are obtained and compared with experimental data and simulation results of other numerical approaches.It is found that SPH simulation can properly reproduce the impact fragmentation of the target and the projectile,and shows advantages over existing numerical approaches in the prediction accuracy of residual mass and velocity.Moreover,effects of some numerical aspects of SPH,including particle spacing,contact treatment and parameters in artificial viscosity and smoothing length,on simulation results are identified.A simple approach using identical smoothing length and balanced artificial viscosity is proposed to reduce particle spacing sensitivity.The observed parametric effects and the proposed approach will provide guidance to set appropriate parameters values for SPH simulation of impact fragmentation.
基金This work was supported by the National Key Research andDevelopment Program of China(No.2018YFA0703000)the National Natural Science Foundation of China(Nos.T2121004,52235007,and 82203602)+2 种基金Zhejiang Provincial Natural Science Foundation of China under Grant No.LQ22H160020 to JWThis work was also supported by Start-up Funding of Zhejiang Provincial People’s Hospital(No.ZRY2021A001 to JW)Basic Scientific Research Funds of Department of Education of Zhejiang Province(No.KYQN202109 to JW).
文摘Prosthesis implantation and fat transplantation are common breast reconstructionmethods.In general,prosthesis implantation alone does not achieve a realistic enough appearance,and fat transplantation alone is difficult to achieve in the correct capacity.To date,no reports have focused on methods of combining fat with implanted prostheses for breast reconstruction.Using a newly designed bionic ink(i.e.,polyether F127 diacrylate(F127DA)&poly(ethylene glycol)diacrylate(PEGDA))and projection-based three-dimensional bioprinting(PBP),we report the development of a new method for printing porous prostheses.PEGDA was used to improve the printing precision of the prosthesis by increasing the gel point of F127DA and reducing the impact of external temperature.The compression modulus of the printed prosthesis was very close to that of prostheses currently used in clinical practice and to that of natural breasts.Finally,stromal vascular fraction gel(SVF-gel),a human fat extract,was injected into the pores of the synthesized prostheses to prepare a prosthesis mixed with adipose tissue.These were implanted subcutaneously in nude mice to observe their biological performance.After 14 and 28 days of observation,the prosthesis showed good biocompatibility,and adipose tissues grew well in and around the prosthesis.This result shows that a porous prosthesis containing pre-placed adipose tissues is a promising breast reconstruction material.
基金supported by the National Natural Science Foundation of China(Grant No.51765020)the Natural Science Foundation of Jiangxi Province(Grant No.20161BAB206153).
文摘Wind turbine is a key device to realize the utilization of wind energy,and it has been highly valued by all countries.But the mechanical gear transmission of the existing wind power device has the disadvantages of high vibration and noise,high failure rate,and short service time.Magneticfield modulation electromagnetic gear transmission is a new non-contact transmission method.However,the conventional modulation magnetic gear has low torque density and torque defects with largefluctuations.In order to overcome the gear transmis-sion problems of the existing semi-direct drive wind power generation machinery and improve the electromag-netic performance of the traditional magnetic gear transmission,this paper proposes a new transmission scheme of a non-contact semi-direct drive wind generator with a surface mount Halbach array modulated mag-netic gear method,and considers the electromagnetic properties of the semi-direct drive modulation magnetic gear of the wind turbine.Thefinite element software is used to construct the model of the surface-mounted Halbach array magnetic gear and the conventional gear,analyzed the distribution of magneticfield lines of the two magnetic gears,calculated the air gap magneticflux density of the inner and outer air gap,and obtained the main harmonics of the inner and outer air gap magnetic density;calculated the static torque and steady-state operating torque of the inner and outer rotors in the model,compared the air gapflux density,harmonics and torque of the magnetic gears.The simulation results show that the magneticfield modulation type mag-netic gear of the surface mount Halbach array magnetic gear method improves the magnetic induction wave-form of the inner and outer air gap,reduces the pulse torquefluctuation,and has a 60%higher static torque.Applying it to semi-direct drive wind power generation equipment not only overcomes the shortcomings of mechanical gears,but also has higher electromagnetic performance.Therefore,the surface-mounted Halbach array modulated magnetic gear can be used to replace the mechanical gearbox in the semi-direct drive wind power generation equipment.
基金supported by National Natural Science Foundation of China(Grant No.52275051)the Natural Science Ranking Projects of Chongqing Jiaotong University(Grant No.XJ2023000701)Team Building Project for Graduate Tutors in Chongqing(Grant No.JDDSTD2022007).
文摘A new type of transportation vehicle,the flying car,is attracting increasing attention in the automotive and aviation industries to meet people’s personalized transportation needs for urban air traffic and future travel.With its vertical take-off and landing capability,flying cars can expand its feasible routes into 3D space.The above process,however,requires sufficient path planning to obtain optimal 3D path.To solve the above issue,the inspiration was drawn from animals in the natural world to design a type of flying car that can travel in various urban environments such as land and low altitude by using different components like wheels and propellers.Incorporating the motion characteristics of flying cars in the future urban environment,segmenting the energy consumption and time models of various stages of flying cars is conducted.The introduction of temporal A*algorithm into the new field of flying cars for the first time,the priority planning algorithm for multiple flying car groups based on an improved A*algorithm utilizing safety intervals is proposed.The proposed strategy is validated on different sizes of urban environment maps.The results indicate that on a complex map with 452 nodes,the strategy effectively reduces distance by 4.5 m,decreases energy consumption by 85.8%and improves planning speed.Compared with the strategy based on multi-commodity network flow integer linear programming,the planning results are roughly the same,but the weighted cost of employing this strategy is decreased by 5.2%,and the path distance is reduced by 0.34 m.
基金supported by Jiangxi Provincial Natural Science Foundation(20252BAC200356).
文摘Dual fuel engine combustion characteristic using the mixture of compressed natural gas(NG) and ethanol as low reactivity fuel and diesel as high reactivity fuel was investigated experimentally in this work.Experiments were performed on an optical engine with double diesel injection strategy using the high-speed natural flame luminosity(NFL) imaging technique,and the flame temperature and soot volume fraction were extracted using the two-color method.NG was added into the ethanol/air mixture as an energy surplus and NG energy rate(NER) was set at 0%,50%,60% and 70%.The diesel pilot injection time(PIT) was set at-24℃A,-18℃A and-12℃A ATDC.Results indicate that adding surplus NG results in a delay in the ignition,growth in the combustion duration and pressure rise rate,an increase of in-cylinder pressure and indicated mean effective pressure(IMEP).Meanwhile,the addition of NG has significant effect on the flame development and soot formation characteristics but their sensitivities to the NER are PIT dependent.At-12℃A ATDC case,the increase in NER results in a substantial decrease in spatially integrated natural luminosity(SINL),flame area(FA)and total soot KL factor(TKL) peaks and a backward shift in the curves of SINL,FA and TKL.But at advanced PIT cases,the SINL,FA and TKL curves obviously grow up as the NER increases.Besides,advancing the PIT results in a longer ignition delay,shorter combustion duration and lower IMEP.Moreover,with advancing the PIT,the TKL peak and time integrated total soot KL factor(IKL) show the tendency of decrease for diesel-ethanol dual fuel.However,for diesel-ethanol-NG ternary fuel,the TKL peak and IKL first increase and then decrease.
基金supported by the Natural Science Foundation of China(52167008)Outstanding Youth Fund Project of Jiangxi Natural Science Foundation(20202ACBL214021)+1 种基金Key Research and Development Plan of Jiangxi Province(20202BBGL73098)Science and Technology Project of Education Department of Jiangxi Province(GJJ210650)。
文摘Aiming at the problems of traditional centralized cloud computing which occupies large computing resources and creates high latency,this paper proposes a fault detection scheme for insulator self-explosion based on edge computing and DL(deep learning).In order to solve the high amount of computation brought by the deep neural network and meet the limited computing resources at the edge,a lightweight SSD(Single Shot MultiBox Detector)target recognition network is designed at the edge,which adopts the MobileNets network to replace VGG16 network in the original model to reduce redundant computing.In the cloud,three detection algorithms(Faster-RCNN,Retinanet,YOLOv3)with obvious differences in detection performance are selected to obtain the coordinates and confidence of the insulator self-explosion area,and then the self-explosion fault detection of the overhead transmission line is realized by a novel multimodel fusion algorithm.The experimental results show that the proposed scheme can effectively reduce the amount of uploaded data,and the average recognition accuracy of the cloud is 95.75%.In addition,it only increases the power consumption of edge devices by about 25.6W/h in their working state.Compared with the existing online monitoring technology of insulator selfexplosion at home and abroad,the proposed scheme has the advantages of low transmission delay,low communication cost and high diagnostic accuracy,which provides a new idea for online monitoring research of power internet of things equipment.
基金supported by the National Natural Science Foundation of China(No.31960497)the Natural Science Foundation of Jiangxi Province(No.20202BAB205009),China.
文摘Background and objectives:Current technology of X-ray imaging can recognize hard foreign materials(FMs)such as metal and high-density plastic.However,low-density foreign bodies are still a challenge for food quality and safety assessment.Materials and methods:An electromagnetic vibration feeder aided by terahertz time-domain spectroscopy(THz-TDS)and imaging was inves-tigated for non-destructively detecting tea stalk and insect FMs mixed with tea leaves.Results:THz time-domain signals were employed directly to develop the K-nearest neighbor model with a precision of 100%,accuracy of 95.6%and recall of 98.7%in predicting the unknown samples.High contrast THz-TDS images were obtained by the separation method for the samples using electromagnetic vibration feeder.The characteristic parameters of the ratio of maximum length(L)to maximum width(W)and hue extracted from THz-TDS images indicated significant difference between tea leaves and FMs.Conclusions:The results suggested that electromagnetic vibration feeder combination with THz-TDS was feasible for detecting FMs in fin-ishingteaproducts.
基金The authors acknowledge the finical support from the Key Laboratory Functional Molecular Solids,Ministry of Education(No.FMS202002)the National Key Research and Development Project(No.2020YFA0210703)+5 种基金the National Natural Science Foundation of China(Nos.U2032158,U2032159,and 62005292)the Key Research and Development Program of Anhui Province(Nos.S202104a05020085 and 201904a05020009)the Science and Technology Service Network Initiative of Chinese Academy of China(grant No.KFJ-STS-ZDTP-080)the Collaborative Innovation Program of Hefei Science Center,CAS(No.2020HSCCIP003)the Major Scientific and the CASHIPS Director’s Fund(No.YZJJZX202015)the Technological Innovation Projects of Shandong Province(No.2019JZZY020243).
文摘Copper sulfide(Cu_(x)S)as a plasmonic solar photothermal semiconductor material that expands the light collection range by altering localized surface plasmon resonance(LSPR)to the near-to mid-infrared(IR)spectral region.The versatile synthesis strategies of Cu_(x)S nanostructure offer its variability of morphology and provide additional freedom in tuning the optical property.Particularly,nanocage(or nanoshell)has hybridized plasmon resonances as a result of super-positioned nanosphere and nanocavity,which extends its receiving range of solar spectrum and increases light-to-heat conversion rate.Here,we offer novel“nanoink”and“nanofilm”developed from colloidal Cu_(27)S_(24)nanocages with excellent solar photothermal response.Via combining experimental measurement and theoretical calculation,we estimated the optical properties of covellite Cu_(27)S_(24).And based on obtained dielectric functions,we then calculated its solar photothermal performance,which was further validated by our experimental measurement.The simulation results showed that hollow Cu_(27)S_(24)nanocages have excellent solar photothermal performance,and exhibit much higher solar photothermal conversion efficiency than solid Cu_(27)S_(24)nanospheres.
基金supported by National Natural Science Foundation of China(52275051)the Natural Science Ranking Projects of Chongqing Jiaotong University(Grant No.XJ2023000701)+2 种基金Team Building Project for Graduate Tutors in Chongqing(Grant No.JDDSTD2022007)Joint Training Base Construction Project for Graduate Students in Chongqing(Grant No.JDLHPYJD2022001)the Natural Science Foundation of Chongqing,China(Grant No.CSTB2022NSCQ-LZX0068).
文摘In order to improve the poor discharge problem that may be caused by the unreasonable power distribution relationship of the battery pack in hybrid vehicles due to the improvement of fuel economy,this paper carries out the research of energy management strategy based on multi-objective optimization for a parallel plug-in hybrid vehicle.The optimization objectives are the optimal fuel economy and the minimum temperature rise of the battery.A vehicle power system model is established to provide a simulation platform for the subsequent verification of the control strategy.A short-term operating condition prediction model is constructed based on the Markov process,ensuring the energy management strategy meets the power balance demand in the local time domain in the future.A multi-objective optimization algorithm is used to enhance the improvement of the traditional equivalent fuel consumption minimization strategy by means of the prediction of the operating conditions,and a real-time search for the optimization is employed by selecting the equivalent factor as the control variable.By selecting the equivalent factor as the control variable for real-time optimization,the optimal time-varying equivalent factor sequence based on multi-objective optimization is obtained,which improves the power distribution between the engine and the motor drive.The results show that the improved control strategy can well trade-off the engine fuel economy and battery temperature rise index,and has excellent battery SOC maintenance capability.While confirming the effectiveness of the strategy,it is verified that it has strong robustness and multi-case generalization capability.
文摘This study employs friction stir welding(FSW)technology to achieve the butt welding of 2mm thick 1060 aluminum and T2 copper.The research investigates the macroscopic formation,tensile properties,microhardness,and electrochemical corrosion behavior of the welded joints.The results indicate that the welded joints exhibit excellent formation,with a tensile strength reaching 84.76%of that of the 1060 aluminum material.Well-formed welded joints can be obtained by controlling the rotation speed and welding speed within a certain range.However,the rotation speed has a more significant impact on the microhardness in the weld zone.The corrosion potential of T2 copper is higher than that of 1060 aluminum,forming a macroscopic galvanic couple between the two materials.The corrosion potential of the welded joint falls between that of T2 copper and 1060 aluminum.
