Surface-enhanced Raman spectroscopy(SERS)has evolved from a laboratory technique to a practical tool for ultra-sensitive detection,particularly in the biomedical field,where precise molecular identification is crucial...Surface-enhanced Raman spectroscopy(SERS)has evolved from a laboratory technique to a practical tool for ultra-sensitive detection,particularly in the biomedical field,where precise molecular identification is crucial.Despite significant advancements,a gap remains in the literature,as no comprehensive review systematically addresses the high-precision construction of SERS substrates for ultrasensitive biomedical detection.This review fills that gap by exploring recent progress in fabricating high-precision SERS substrates,emphasizing their role in enabling ultrasensitive bio-medical sensors.We carefully examine the key to these advancements is the precision engineering of substrates,including noble metals,semiconductors,carbon-based materials,and two-dimensional materials,which is essential for achieving the high sensitivity required for ultrasensitive detection.Applications in biomedical diagnostics and molecular analysis are highlighted.Finally,we address the challenges in SERS substrate preparation and outline future directions,focusing on improvement strategies,design concepts,and expanding applications for these advanced materials.展开更多
Large-aperture optical components are of paramount importance in domains such as integrated circuits,photolithography,aerospace,and inertial confinement fusion.However,measuring their surface profiles relies predomina...Large-aperture optical components are of paramount importance in domains such as integrated circuits,photolithography,aerospace,and inertial confinement fusion.However,measuring their surface profiles relies predominantly on the phase-shifting approach,which involves collecting multiple interferograms and imposes stringent demands on environmental stability.These issues significantly hinder its ability to achieve real-time and dynamic high-precision measurements.Therefore,this study proposes a high-precision large-aperture single-frame interferometric surface profile measurement(LA-SFISPM)method based on deep learning and explores its capability to realize dynamic measurements with high accuracy.The interferogram is matched to the phase by training the data measured using the small aperture.The consistency of the surface features of the small and large apertures is enhanced via contrast learning and feature-distribution alignment.Hence,high-precision phase reconstruction of large-aperture optical components can be achieved without using a phase shifter.The experimental results show that for the tested mirror withΦ=820 mm,the surface profile obtained from LA-SFISPM is subtracted point-by-point from the ground truth,resulting in a maximum single-point error of 4.56 nm.Meanwhile,the peak-to-valley(PV)value is 0.0758λ,and the simple repeatability of root mean square(SR-RMS)value is 0.00025λ,which aligns well with the measured results obtained by ZYGO.In particular,a significant reduction in the measurement time(reduced by a factor of 48)is achieved compared with that of the traditional phase-shifting method.Our proposed method provides an efficient,rapid,and accurate method for obtaining the surface profiles of optical components with different diameters without employing a phase-shifting approach,which is highly desired in large-aperture interferometric measurement systems.展开更多
The elliptic integral method(EIM) is an efficient analytical approach for analyzing large deformations of elastic beams. However, it faces the following challenges.First, the existing EIM can only handle cases with kn...The elliptic integral method(EIM) is an efficient analytical approach for analyzing large deformations of elastic beams. However, it faces the following challenges.First, the existing EIM can only handle cases with known deformation modes. Second,the existing EIM is only applicable to Euler beams, and there is no EIM available for higher-precision Timoshenko and Reissner beams in cases where both force and moment are applied at the end. This paper proposes a general EIM for Reissner beams under arbitrary boundary conditions. On this basis, an analytical equation for determining the sign of the elliptic integral is provided. Based on the equation, we discover a class of elliptic integral piecewise points that are distinct from inflection points. More importantly, we propose an algorithm that automatically calculates the number of inflection points and other piecewise points during the nonlinear solution process, which is crucial for beams with unknown or changing deformation modes.展开更多
Earth sensors are widely used in spacecraft for attitude determination. They need to have a very large field of view(FOV)( > 120°) and relatively low accuracy while being used in the aircrafts around orbit. A ...Earth sensors are widely used in spacecraft for attitude determination. They need to have a very large field of view(FOV)( > 120°) and relatively low accuracy while being used in the aircrafts around orbit. A triple-FOV infrared earth sensor is proposed in this paper. It uses three pieces of standard infrared detectors with a wavelength range of 14;16μm,to sense the horizontal circle by detecting the infrared light emitted from the earth. From which,the geocentric vector can be obtained. A mathematic model is established and a validation model is set up to provide input parameters for the mathematic model. The simulation results of the two models show that the output of the mathematic model coincides with the known parameters. Based on the above analysis,a prototype has been built and tested. The test results show that the angle measurement error is about 0. 002° and hence such a triple-FOV earth sensor is capable to provide high-precision position information for autonomous navigation.展开更多
With the intensifying competition in the integrated circuit(IC)industry,the high turnover rate of integrated circuit engineers has become a prominent issue affecting the technological continuity of high-precision,spec...With the intensifying competition in the integrated circuit(IC)industry,the high turnover rate of integrated circuit engineers has become a prominent issue affecting the technological continuity of high-precision,specialized,and innovative enterprises.As a representative of such enterprises,JL Technology has faced challenges to its R&D efficiency due to talent loss in recent years.This study takes this enterprise as a case to explore feasible paths to reduce turnover rates through optimizing training and career development systems.The research designs a method combining learning maps and talent maps,utilizes a competency model to clarify the direction for engineers’skill improvement,implements talent classification management using a nine-grid model,and achieves personalized training through Individual Development Plans(IDPs).Analysis of the enterprise’s historical data reveals that the main reasons for turnover are unclear career development paths and insufficient resources for skill improvement.After pilot implementation,the turnover rate in core departments decreased by 12%,and employee satisfaction with training increased by 24%.The results indicate that matching systematic talent reviews with dynamic learning resources can effectively enhance engineers’sense of belonging.This study provides a set of highly operational management tools for small and medium-sized high-precision,specialized,and innovative technology enterprises,verifies their applicability in such enterprises,and offers replicable experiences for similar enterprises to optimize their talent strategies[1].展开更多
Highly sensitive and stable acetylcholinesterase detection is critical for diagnosing and treating various neurotransmission-related diseases.In this study,a novel colorimetric-fluorescent dual-mode biosensor based on...Highly sensitive and stable acetylcholinesterase detection is critical for diagnosing and treating various neurotransmission-related diseases.In this study,a novel colorimetric-fluorescent dual-mode biosensor based on highly dispersive trimetal-modified graphite-phase carbon nitride nanocomposites for acetylcholinesterase detection was designed and synthesized by phosphorus doping and a mixed-metal MOF strategy.The specific surface area of trimetal-modified graphite-phase carbon nitride nanocomposites increased from 15.81 to 96.69 g m^(-2),and its thermal stability,interfacial charge transfer,and oxidation-reduction capability were enhanced compared with those of graphite-phase carbon nitride.First-principles density functional theory calculations and steady-state kinetic analysis are applied to investigate the electronic structures and efficient peroxidase-mimicking properties of trimetal-modified graphite-phase carbon nitride nanocomposites.The oxidation of 3,3',5,5'-tetramethylbenzidin was inhibited by thiocholine,which originates from the decomposition of thiocholine iodide by Acetyl-cholinesterase(AChE),resulting in changes in fluorescence and absorbance intensity.Due to the independence and complementarity of the signals,a highly precise colorimetric-fluorescent dual-mode biosensor with a linear range for detecting AChE of 4-20μU mL^(-1) and detection limits of 0.13μU mL^(-1)(colorimetric)and 0.04μU mL^(-1)(fluorescence)was developed.The spiking recovery of AChE in actual samples was 99.0%-100.4%.Therefore,a highly accurate,specific,and stable dual-mode biosensor is available for AChE detection,and this biosensor has the potential for the analysis of other biomarkers.展开更多
Flexible fiber sensors,However,traditional methods face challenges in fabricating low-cost,large-scale fiber sensors.In recent years,the thermal drawing process has rapidly advanced,offering a novel approach to flexib...Flexible fiber sensors,However,traditional methods face challenges in fabricating low-cost,large-scale fiber sensors.In recent years,the thermal drawing process has rapidly advanced,offering a novel approach to flexible fiber sensors.Through the preform-tofiber manufacturing technique,a variety of fiber sensors with complex functionalities spanning from the nanoscale to kilometer scale can be automated in a short time.Examples include temperature,acoustic,mechanical,chemical,biological,optoelectronic,and multifunctional sensors,which operate on diverse sensing principles such as resistance,capacitance,piezoelectricity,triboelectricity,photoelectricity,and thermoelectricity.This review outlines the principles of the thermal drawing process and provides a detailed overview of the latest advancements in various thermally drawn fiber sensors.Finally,the future developments of thermally drawn fiber sensors are discussed.展开更多
Wearable sensors integrated with deep learning techniques have the potential to revolutionize seamless human-machine interfaces for real-time health monitoring,clinical diagnosis,and robotic applications.Nevertheless,...Wearable sensors integrated with deep learning techniques have the potential to revolutionize seamless human-machine interfaces for real-time health monitoring,clinical diagnosis,and robotic applications.Nevertheless,it remains a critical challenge to simultaneously achieve desirable mechanical and electrical performance along with biocompatibility,adhesion,self-healing,and environmental robustness with excellent sensing metrics.Herein,we report a multifunctional,anti-freezing,selfadhesive,and self-healable organogel pressure sensor composed of cobalt nanoparticle encapsulated nitrogen-doped carbon nanotubes(CoN CNT)embedded in a polyvinyl alcohol-gelatin(PVA/GLE)matrix.Fabricated using a binary solvent system of water and ethylene glycol(EG),the CoN CNT/PVA/GLE organogel exhibits excellent flexibility,biocompatibility,and temperature tolerance with remarkable environmental stability.Electrochemical impedance spectroscopy confirms near-stable performance across a broad humidity range(40%-95%RH).Freeze-tolerant conductivity under sub-zero conditions(-20℃)is attributed to the synergistic role of CoN CNT and EG,preserving mobility and network integrity.The Co N CNT/PVA/GLE organogel sensor exhibits high sensitivity of 5.75 k Pa^(-1)in the detection range from 0 to 20 k Pa,ideal for subtle biomechanical motion detection.A smart human-machine interface for English letter recognition using deep learning achieved 98%accuracy.The organogel sensor utility was extended to detect human gestures like finger bending,wrist motion,and throat vibration during speech.展开更多
As emerging two-dimensional(2D)materials,carbides and nitrides(MXenes)could be solid solutions or organized structures made up of multi-atomic layers.With remarkable and adjustable electrical,optical,mechanical,and el...As emerging two-dimensional(2D)materials,carbides and nitrides(MXenes)could be solid solutions or organized structures made up of multi-atomic layers.With remarkable and adjustable electrical,optical,mechanical,and electrochemical characteristics,MXenes have shown great potential in brain-inspired neuromorphic computing electronics,including neuromorphic gas sensors,pressure sensors and photodetectors.This paper provides a forward-looking review of the research progress regarding MXenes in the neuromorphic sensing domain and discussed the critical challenges that need to be resolved.Key bottlenecks such as insufficient long-term stability under environmental exposure,high costs,scalability limitations in large-scale production,and mechanical mismatch in wearable integration hinder their practical deployment.Furthermore,unresolved issues like interfacial compatibility in heterostructures and energy inefficiency in neu-romorphic signal conversion demand urgent attention.The review offers insights into future research directions enhance the fundamental understanding of MXene properties and promote further integration into neuromorphic computing applications through the convergence with various emerging technologies.展开更多
Diabetes mellitus represents a major global health issue,driving the need for noninvasive alternatives to traditional blood glucose monitoring methods.Recent advancements in wearable technology have introduced skin-in...Diabetes mellitus represents a major global health issue,driving the need for noninvasive alternatives to traditional blood glucose monitoring methods.Recent advancements in wearable technology have introduced skin-interfaced biosensors capable of analyzing sweat and skin biomarkers,providing innovative solutions for diabetes diagnosis and monitoring.This review comprehensively discusses the current developments in noninvasive wearable biosensors,emphasizing simultaneous detection of biochemical biomarkers(such as glucose,cortisol,lactate,branched-chain amino acids,and cytokines)and physiological signals(including heart rate,blood pressure,and sweat rate)for accurate,personalized diabetes management.We explore innovations in multimodal sensor design,materials science,biorecognition elements,and integration techniques,highlighting the importance of advanced data analytics,artificial intelligence-driven predictive algorithms,and closed-loop therapeutic systems.Additionally,the review addresses ongoing challenges in biomarker validation,sensor stability,user compliance,data privacy,and regulatory considerations.A holistic,multimodal approach enabled by these next-generation wearable biosensors holds significant potential for improving patient outcomes and facilitating proactive healthcare interventions in diabetes management.展开更多
Human action recognition(HAR)is crucial for the development of efficient computer vision,where bioinspired neuromorphic perception visual systems have emerged as a vital solution to address transmission bottlenecks ac...Human action recognition(HAR)is crucial for the development of efficient computer vision,where bioinspired neuromorphic perception visual systems have emerged as a vital solution to address transmission bottlenecks across sensor-processor interfaces.However,the absence of interactions among versatile biomimicking functionalities within a single device,which was developed for specific vision tasks,restricts the computational capacity,practicality,and scalability of in-sensor vision computing.Here,we propose a bioinspired vision sensor composed of a Ga N/Al N-based ultrathin quantum-disks-in-nanowires(QD-NWs)array to mimic not only Parvo cells for high-contrast vision and Magno cells for dynamic vision in the human retina but also the synergistic activity between the two cells for in-sensor vision computing.By simply tuning the applied bias voltage on each QD-NW-array-based pixel,we achieve two biosimilar photoresponse characteristics with slow and fast reactions to light stimuli that enhance the in-sensor image quality and HAR efficiency,respectively.Strikingly,the interplay and synergistic interaction of the two photoresponse modes within a single device markedly increased the HAR recognition accuracy from 51.4%to 81.4%owing to the integrated artificial vision system.The demonstration of an intelligent vision sensor offers a promising device platform for the development of highly efficient HAR systems and future smart optoelectronics.展开更多
The growing prevalence of exercise-induced tibial stress fractures demands wearable sensors capable of monitoring dynamic musculoskeletal loads with medical-grade precision.While flexible pressure-sensing insoles show...The growing prevalence of exercise-induced tibial stress fractures demands wearable sensors capable of monitoring dynamic musculoskeletal loads with medical-grade precision.While flexible pressure-sensing insoles show clinical potential,their development has been hindered by the intrinsic trade-off between high sensitivity and full-range linearity(R^(2)>0.99 up to 1 MPa)in conventional designs.Inspired by the tactile sensing mechanism of human skin,where dermal stratification enables wide-range pressure adaptation and ion-channelregulated signaling maintains linear electrical responses,we developed a dual-mechanism flexible iontronic pressure sensor(FIPS).This innovative design synergistically combines two bioinspired components:interdigitated fabric microstructures enabling pressure-proportional contact area expansion(αP1/3)and iontronic film facilitating self-adaptive ion concentration modulation(αP^(2/3)),which together generate a linear capacitance-pressure response(CαP).The FIPS achieves breakthrough performance:242 kPa^(-1)sensitivity with 0.997linearity across 0-1 MPa,yielding a record linear sensing factor(LSF=242,000).The design is validated across various substrates and ionic materials,demonstrating its versatility.Finally,the FIPS-driven design enables a smart insole demonstrating 1.8%error in tibial load assessment during gait analysis,outperforming nonlinear counterparts(6.5%error)in early fracture-risk prediction.The biomimetic design framework establishes a universal approach for developing high-performance linear sensors,establishing generalized principles for medical-grade wearable devices.展开更多
To realize high-precision automatic measurement of two-dimensional geometric features on parts, a cooperative measurement system based on machine vision is constructed. Its hardware structure, functional composition a...To realize high-precision automatic measurement of two-dimensional geometric features on parts, a cooperative measurement system based on machine vision is constructed. Its hardware structure, functional composition and working principle are introduced. The mapping relationship between the feature image coordinates and the measuring space coordinates is established. The method of measuring path planning of small field of view （FOV） images is proposed. With the cooperation of the panoramic image of the object to be measured, the small FOV images with high object plane resolution are acquired automatically. Then, the auxiliary measuring characteristics are constructed and the parameters of the features to be measured are automatically extracted. Experimental results show that the absolute value of relative error is less than 0. 03% when applying the cooperative measurement system to gauge the hole distance of 100 mm nominal size. When the object plane resolving power of the small FOV images is 16 times that of the large FOV image, the measurement accuracy of small FOV images is improved by 14 times compared with the large FOV image. It is suitable for high-precision automatic measurement of two-dimensional complex geometric features distributed on large scale parts.展开更多
Multi-sensor coordinate unification in dimensional metrology is used in order to get holistic, more accurate and reliable information about a workpiece based on several or multiple measurement values from ...Multi-sensor coordinate unification in dimensional metrology is used in order to get holistic, more accurate and reliable information about a workpiece based on several or multiple measurement values from one or more sensors. Because of the problem that standard ball is deficient as a standard artifact in the coordinate unification of high-precision composite measurement in two dimensions （2D） , a new method is proposed in this paper which uses angle gauge blocks as standard artifacts to achieve coordinate unification between the image sensor and the tactile probe. By comparing the standard ball with the angle gauge block as a standard artifact, theoretical analysis and experimental results are given to prove that it is more precise and more convenient to use angle gauge blocks as standard artifacts to achieve coordinate unification of high-precision composite measurement in two dimensions.展开更多
The Tibetan Plateau(TP)is the youngest orogenic belt resulting from a continental collision on the Earth.It is a natural laboratory for studying continental dynamics,such as continental convergence,plate subduction,an...The Tibetan Plateau(TP)is the youngest orogenic belt resulting from a continental collision on the Earth.It is a natural laboratory for studying continental dynamics,such as continental convergence,plate subduction,and plateau uplift.Investigating the deep structure of the TP has always been a popular issue in geological research.The Moho is the boundary between the crust and the mantle and therefore plays a crucial role in the Earth’s structure.Parameters such as depth and lateral variation,as well as the fine structure of the crust-mantle interface,reveal the lithospheric dynamics in the TP.Two methods are generally employed to study the Moho surface:seismic detection and gravity inversion.Seismic detection has the characteristic of high precision,but it is limited to a few cross-sectional lines and is quite costly.It is not suitable for and cannot be carried out over a large area of the TP.The Moho depth over a large area can be obtained through gravity inversion,but this method is affected by the nature of gravity data,and the accuracy of the inversion method is lower than that of seismic detection.In this work,a high-precision gravity field model was selected.The Parker-Oldenburg interface inversion method was used,within the constraints of seismic observations,and the Bott iteration method was introduced to enhance the inversion efficiency.The Moho depth in the TP was obtained with high precision,consistent with the seismic detection results.The research results showed that the shape of the Moho in the TP is complex and the variation range is large,reaching 60−80 km.In contrast with the adjacent area,a clear zone of sharp variation appears at the edge of the plateau.In the interior of the TP,the buried depth of the Moho is characterized by two depressions and two uplifts.To the south of the Yarlung Zangbo River,the Moho inclines to the north,and to the north,the Moho depresses downward,which was interpreted as the Indian plate subducting to the north below Xizang.The Moho depression on the north side of the Qiangtang block,reaching 72 km deep,may be a result of the southward subduction of the lithosphere.The Moho uplift of the Qiangtang block has the same strike as the Bangong−Nujiang suture zone,which may indicate that the area is compensated by a low-density and low-velocity mantle.展开更多
A reliable multiphase flow simulator is an important tool to improve wellbore integrity and production decision-making.To develop a multiphase flow model with high adaptability and high accuracy,we first build a multi...A reliable multiphase flow simulator is an important tool to improve wellbore integrity and production decision-making.To develop a multiphase flow model with high adaptability and high accuracy,we first build a multiphase flow database with 3561 groups of data and developed a drift closure relationship with stable continuity and high adaptability.Second,a high-order numerical scheme with strong fault capture ability is constructed by effectively combining MUSCL technology,van Albada slope limiter and AUSMV numerical scheme.Finally,the energy equation is coupled into the AUSMV numerical scheme of the drift flow model in the form of finite difference.A transient non-isothermal wellbore multiphase flow model with wide applicability is formed by integrating the three technologies,and the effects of various factors on the calculation accuracy are studied.The accuracy of the simulator is verified by comparing the measurement results with the blowout experiment of a full-scale experimental well.展开更多
The magnetic field is one of the most important parameters in solar physics,and a polarimeter is the key device to measure the solar magnetic field.Liquid crystals based Stokes polarimeter is a novel technology,and wi...The magnetic field is one of the most important parameters in solar physics,and a polarimeter is the key device to measure the solar magnetic field.Liquid crystals based Stokes polarimeter is a novel technology,and will be applied for magnetic field measurement in the first space-based solar observatory satellite developed by China,Advanced Space-based Solar Observatory.However,the liquid crystals based Stokes polarimeter in space is not a mature technology.Therefore,it is of great scientific significance to study the control method and characteristics of the device.The retardation produced by a liquid crystal variable retarder is sensitive to the temperature,and the retardation changes 0.09°per 0.10℃.The error in polarization measurement caused by this change is 0.016,which affects the accuracy of magnetic field measurement.In order to ensure the stability of its performance,this paper proposes a high-precision temperature control system for liquid crystals based Stokes polarimeter in space.In order to optimize the structure design and temperature control system,the temperature field of liquid crystals based Stokes polarimeter is analyzed by the finite element method,and the influence of light on the temperature field of the liquid crystal variable retarder is analyzed theoretically.By analyzing the principle of highprecision temperature measurement in space,a high-precision temperature measurement circuit based on integrated operational amplifier,programmable amplifier and 12 bit A/D is designed,and a high-precision space temperature control system is developed by applying the integral separation PI temperature control algorithm and PWM driving heating films.The experimental results show that the effect of temperature control is accurate and stable,whenever the liquid crystals based Stokes polarimeter is either in the air or vacuum.The temperature stability is within±0.0150℃,which demonstrates greatly improved stability for the liquid crystals based Stokes polarimeter.展开更多
High-precision turning(HPT)is a main processing method for manufacturing rotary high-precision components,especially for metallic parts.However,the generated vibration between tool tip and workpiece during turning may...High-precision turning(HPT)is a main processing method for manufacturing rotary high-precision components,especially for metallic parts.However,the generated vibration between tool tip and workpiece during turning may seriously deteriorate the surface integrity.Therefore,exploring the effect of vibration on turning surface morphology and quality of copper parts using 3D surface topography regeneration model is crucial for predicting HPT performance.This developed model can update the machined surface topology in real time.In this study,the effects of tool arc radius,feed rate,radial vibration,axial vibration and tangential vibration on the surface topography and surface roughness were explored.The results show that the effect of radial vibration on surface topography is greater than that of axial vibration and tangential vibration.The radial vibration frequency is also critical.When vibration frequency changes,the surface topography profile presents three different types:the standard sinusoidal curve,the sinusoidal curve whose lowfrequency signal envelopes high-frequency signal,and the oscillation curve whose low-frequency signal superimposes high-frequency signal.In addition,HPT experiment was carried out to validate the developed model.The surface roughness obtained in the experiment was Ra=53 nm,while the roughness obtained by the simulation was Ra=46 nm,achieving a prediction accuracy of 86.7%.Received 4 September 2022;revised 3 October 2022;accepted 17 October 2022.展开更多
This paper introduces a design of high-precision high-voltage fiber-optic analog sig-nal isolation converter based on the technology of Voltage-to-Frequency (V/F) and Frequency-to-Voltage (F/V) conversion. It describe...This paper introduces a design of high-precision high-voltage fiber-optic analog sig-nal isolation converter based on the technology of Voltage-to-Frequency (V/F) and Frequency-to-Voltage (F/V) conversion. It describes the principle, system configuration and hardware design.展开更多
High-precision lane keeping is essential for the future autonomous driving.However,due to the imbalanced and inaccurate datasets collected by human drivers,current end-to-end driving models have poor lane keeping the ...High-precision lane keeping is essential for the future autonomous driving.However,due to the imbalanced and inaccurate datasets collected by human drivers,current end-to-end driving models have poor lane keeping the effect.To improve the precision of lane keeping,this study presents a novel multi-state model-based end-to-end lane keeping method.First,three driving states will be defined:going straight,turning right and turning left.Second,the finite-state machine(FSM)table as well as three kinds of training datasets will be generated based on the three driving states.Instead of collecting the dataset by human drivers,the accurate dataset will be collected by the high-performance path following controller.Third,three sets of parameters based on 3DCNN-LSTM model will be trained for going straight,turning left and turning right,which will be combined with FSM table to form a multi-state model.This study evaluates the multi-state model by testing it on five tracks and recording the lane keeping error.The result shows the multi-state model-based end-to-end method performs the higher precision of lane keeping than the traditional single end-to-end model.展开更多
基金supported by the projects funded by the Education Department of Shaanxi Provincial Government(NO.23JP116)the Natural Science Fund of Shaanxi Province(NO.2024JC-YBMS-396)+3 种基金the National Natural Science Foundation of China(NO.52171191,52371198,U22A20137)the Constructing National Independent Innovation Demonstration Zones(XM2024XTGXQ05)Shenzhen Science and Technology Innovation Program(JCYJ20220818102215033,GJHZ20210705142542015,JCYJ20220530160811027)Guangdong HUST Industrial Technology Research Institute,Guangdong Provincial Key Laboratory of Manufacturing Equipment Digitization(2023B1212060012).
文摘Surface-enhanced Raman spectroscopy(SERS)has evolved from a laboratory technique to a practical tool for ultra-sensitive detection,particularly in the biomedical field,where precise molecular identification is crucial.Despite significant advancements,a gap remains in the literature,as no comprehensive review systematically addresses the high-precision construction of SERS substrates for ultrasensitive biomedical detection.This review fills that gap by exploring recent progress in fabricating high-precision SERS substrates,emphasizing their role in enabling ultrasensitive bio-medical sensors.We carefully examine the key to these advancements is the precision engineering of substrates,including noble metals,semiconductors,carbon-based materials,and two-dimensional materials,which is essential for achieving the high sensitivity required for ultrasensitive detection.Applications in biomedical diagnostics and molecular analysis are highlighted.Finally,we address the challenges in SERS substrate preparation and outline future directions,focusing on improvement strategies,design concepts,and expanding applications for these advanced materials.
基金funded by the National Natural Science Foundation of China Instrumentation Program(52327806)Youth Fund of the National Nature Foundation of China(62405020)China Postdoctoral Science Foundation(2024M764131).
文摘Large-aperture optical components are of paramount importance in domains such as integrated circuits,photolithography,aerospace,and inertial confinement fusion.However,measuring their surface profiles relies predominantly on the phase-shifting approach,which involves collecting multiple interferograms and imposes stringent demands on environmental stability.These issues significantly hinder its ability to achieve real-time and dynamic high-precision measurements.Therefore,this study proposes a high-precision large-aperture single-frame interferometric surface profile measurement(LA-SFISPM)method based on deep learning and explores its capability to realize dynamic measurements with high accuracy.The interferogram is matched to the phase by training the data measured using the small aperture.The consistency of the surface features of the small and large apertures is enhanced via contrast learning and feature-distribution alignment.Hence,high-precision phase reconstruction of large-aperture optical components can be achieved without using a phase shifter.The experimental results show that for the tested mirror withΦ=820 mm,the surface profile obtained from LA-SFISPM is subtracted point-by-point from the ground truth,resulting in a maximum single-point error of 4.56 nm.Meanwhile,the peak-to-valley(PV)value is 0.0758λ,and the simple repeatability of root mean square(SR-RMS)value is 0.00025λ,which aligns well with the measured results obtained by ZYGO.In particular,a significant reduction in the measurement time(reduced by a factor of 48)is achieved compared with that of the traditional phase-shifting method.Our proposed method provides an efficient,rapid,and accurate method for obtaining the surface profiles of optical components with different diameters without employing a phase-shifting approach,which is highly desired in large-aperture interferometric measurement systems.
基金supported by the National Natural Science Foundation of China (Nos. 12172388 and 12472400)the Guangdong Basic and Applied Basic Research Foundation of China(No. 2025A1515011975)the Scientific Research Project of Guangdong Polytechnic Normal University of China (No. 2023SDKYA010)
文摘The elliptic integral method(EIM) is an efficient analytical approach for analyzing large deformations of elastic beams. However, it faces the following challenges.First, the existing EIM can only handle cases with known deformation modes. Second,the existing EIM is only applicable to Euler beams, and there is no EIM available for higher-precision Timoshenko and Reissner beams in cases where both force and moment are applied at the end. This paper proposes a general EIM for Reissner beams under arbitrary boundary conditions. On this basis, an analytical equation for determining the sign of the elliptic integral is provided. Based on the equation, we discover a class of elliptic integral piecewise points that are distinct from inflection points. More importantly, we propose an algorithm that automatically calculates the number of inflection points and other piecewise points during the nonlinear solution process, which is crucial for beams with unknown or changing deformation modes.
基金financially supported by the National High Technology Research and Development Program of China(863 Program)(No.2012AA121503 and No.2012AA120603)the National Natural Science Foundation of China(No.61377012)the Tsinghua University Initiative Scientific Research Program(No.20131089242)。
文摘Earth sensors are widely used in spacecraft for attitude determination. They need to have a very large field of view(FOV)( > 120°) and relatively low accuracy while being used in the aircrafts around orbit. A triple-FOV infrared earth sensor is proposed in this paper. It uses three pieces of standard infrared detectors with a wavelength range of 14;16μm,to sense the horizontal circle by detecting the infrared light emitted from the earth. From which,the geocentric vector can be obtained. A mathematic model is established and a validation model is set up to provide input parameters for the mathematic model. The simulation results of the two models show that the output of the mathematic model coincides with the known parameters. Based on the above analysis,a prototype has been built and tested. The test results show that the angle measurement error is about 0. 002° and hence such a triple-FOV earth sensor is capable to provide high-precision position information for autonomous navigation.
文摘With the intensifying competition in the integrated circuit(IC)industry,the high turnover rate of integrated circuit engineers has become a prominent issue affecting the technological continuity of high-precision,specialized,and innovative enterprises.As a representative of such enterprises,JL Technology has faced challenges to its R&D efficiency due to talent loss in recent years.This study takes this enterprise as a case to explore feasible paths to reduce turnover rates through optimizing training and career development systems.The research designs a method combining learning maps and talent maps,utilizes a competency model to clarify the direction for engineers’skill improvement,implements talent classification management using a nine-grid model,and achieves personalized training through Individual Development Plans(IDPs).Analysis of the enterprise’s historical data reveals that the main reasons for turnover are unclear career development paths and insufficient resources for skill improvement.After pilot implementation,the turnover rate in core departments decreased by 12%,and employee satisfaction with training increased by 24%.The results indicate that matching systematic talent reviews with dynamic learning resources can effectively enhance engineers’sense of belonging.This study provides a set of highly operational management tools for small and medium-sized high-precision,specialized,and innovative technology enterprises,verifies their applicability in such enterprises,and offers replicable experiences for similar enterprises to optimize their talent strategies[1].
基金supported by the Hubei University of Technology Graduate Research Innovation Project(No.2022048)the Natural Science Foundation Project of Hubei Province(grant No.2022CFB533)+1 种基金the Scientific Research Plan of Education Department of Hubei Province(grant No.D20222702)the Natural Science Project of Xiaogan city(grant No.XGKJ20210100014).
文摘Highly sensitive and stable acetylcholinesterase detection is critical for diagnosing and treating various neurotransmission-related diseases.In this study,a novel colorimetric-fluorescent dual-mode biosensor based on highly dispersive trimetal-modified graphite-phase carbon nitride nanocomposites for acetylcholinesterase detection was designed and synthesized by phosphorus doping and a mixed-metal MOF strategy.The specific surface area of trimetal-modified graphite-phase carbon nitride nanocomposites increased from 15.81 to 96.69 g m^(-2),and its thermal stability,interfacial charge transfer,and oxidation-reduction capability were enhanced compared with those of graphite-phase carbon nitride.First-principles density functional theory calculations and steady-state kinetic analysis are applied to investigate the electronic structures and efficient peroxidase-mimicking properties of trimetal-modified graphite-phase carbon nitride nanocomposites.The oxidation of 3,3',5,5'-tetramethylbenzidin was inhibited by thiocholine,which originates from the decomposition of thiocholine iodide by Acetyl-cholinesterase(AChE),resulting in changes in fluorescence and absorbance intensity.Due to the independence and complementarity of the signals,a highly precise colorimetric-fluorescent dual-mode biosensor with a linear range for detecting AChE of 4-20μU mL^(-1) and detection limits of 0.13μU mL^(-1)(colorimetric)and 0.04μU mL^(-1)(fluorescence)was developed.The spiking recovery of AChE in actual samples was 99.0%-100.4%.Therefore,a highly accurate,specific,and stable dual-mode biosensor is available for AChE detection,and this biosensor has the potential for the analysis of other biomarkers.
基金supported by the National Key Research and Development Program of China(2023YFB3809800)the National Natural Science Foundation of China(52172249,52525601)+2 种基金the Chinese Academy of Sciences Talents Program(E2290701)the Jiangsu Province Talents Program(JSSCRC2023545)the Special Fund Project of Carbon Peaking Carbon Neutrality Science and Technology Innovation of Jiangsu Province(BE2022011).
文摘Flexible fiber sensors,However,traditional methods face challenges in fabricating low-cost,large-scale fiber sensors.In recent years,the thermal drawing process has rapidly advanced,offering a novel approach to flexible fiber sensors.Through the preform-tofiber manufacturing technique,a variety of fiber sensors with complex functionalities spanning from the nanoscale to kilometer scale can be automated in a short time.Examples include temperature,acoustic,mechanical,chemical,biological,optoelectronic,and multifunctional sensors,which operate on diverse sensing principles such as resistance,capacitance,piezoelectricity,triboelectricity,photoelectricity,and thermoelectricity.This review outlines the principles of the thermal drawing process and provides a detailed overview of the latest advancements in various thermally drawn fiber sensors.Finally,the future developments of thermally drawn fiber sensors are discussed.
基金supported by the Basic Science Research Program(2023R1A2C3004336,RS-202300243807)&Regional Leading Research Center(RS-202400405278)through the National Research Foundation of Korea(NRF)grant funded by the Korea Government(MSIT)。
文摘Wearable sensors integrated with deep learning techniques have the potential to revolutionize seamless human-machine interfaces for real-time health monitoring,clinical diagnosis,and robotic applications.Nevertheless,it remains a critical challenge to simultaneously achieve desirable mechanical and electrical performance along with biocompatibility,adhesion,self-healing,and environmental robustness with excellent sensing metrics.Herein,we report a multifunctional,anti-freezing,selfadhesive,and self-healable organogel pressure sensor composed of cobalt nanoparticle encapsulated nitrogen-doped carbon nanotubes(CoN CNT)embedded in a polyvinyl alcohol-gelatin(PVA/GLE)matrix.Fabricated using a binary solvent system of water and ethylene glycol(EG),the CoN CNT/PVA/GLE organogel exhibits excellent flexibility,biocompatibility,and temperature tolerance with remarkable environmental stability.Electrochemical impedance spectroscopy confirms near-stable performance across a broad humidity range(40%-95%RH).Freeze-tolerant conductivity under sub-zero conditions(-20℃)is attributed to the synergistic role of CoN CNT and EG,preserving mobility and network integrity.The Co N CNT/PVA/GLE organogel sensor exhibits high sensitivity of 5.75 k Pa^(-1)in the detection range from 0 to 20 k Pa,ideal for subtle biomechanical motion detection.A smart human-machine interface for English letter recognition using deep learning achieved 98%accuracy.The organogel sensor utility was extended to detect human gestures like finger bending,wrist motion,and throat vibration during speech.
基金supported by the NSFC(12474071)Natural Science Foundation of Shandong Province(ZR2024YQ051,ZR2025QB50)+6 种基金Guangdong Basic and Applied Basic Research Foundation(2025A1515011191)the Shanghai Sailing Program(23YF1402200,23YF1402400)funded by Basic Research Program of Jiangsu(BK20240424)Open Research Fund of State Key Laboratory of Crystal Materials(KF2406)Taishan Scholar Foundation of Shandong Province(tsqn202408006,tsqn202507058)Young Talent of Lifting engineering for Science and Technology in Shandong,China(SDAST2024QTB002)the Qilu Young Scholar Program of Shandong University。
文摘As emerging two-dimensional(2D)materials,carbides and nitrides(MXenes)could be solid solutions or organized structures made up of multi-atomic layers.With remarkable and adjustable electrical,optical,mechanical,and electrochemical characteristics,MXenes have shown great potential in brain-inspired neuromorphic computing electronics,including neuromorphic gas sensors,pressure sensors and photodetectors.This paper provides a forward-looking review of the research progress regarding MXenes in the neuromorphic sensing domain and discussed the critical challenges that need to be resolved.Key bottlenecks such as insufficient long-term stability under environmental exposure,high costs,scalability limitations in large-scale production,and mechanical mismatch in wearable integration hinder their practical deployment.Furthermore,unresolved issues like interfacial compatibility in heterostructures and energy inefficiency in neu-romorphic signal conversion demand urgent attention.The review offers insights into future research directions enhance the fundamental understanding of MXene properties and promote further integration into neuromorphic computing applications through the convergence with various emerging technologies.
文摘Diabetes mellitus represents a major global health issue,driving the need for noninvasive alternatives to traditional blood glucose monitoring methods.Recent advancements in wearable technology have introduced skin-interfaced biosensors capable of analyzing sweat and skin biomarkers,providing innovative solutions for diabetes diagnosis and monitoring.This review comprehensively discusses the current developments in noninvasive wearable biosensors,emphasizing simultaneous detection of biochemical biomarkers(such as glucose,cortisol,lactate,branched-chain amino acids,and cytokines)and physiological signals(including heart rate,blood pressure,and sweat rate)for accurate,personalized diabetes management.We explore innovations in multimodal sensor design,materials science,biorecognition elements,and integration techniques,highlighting the importance of advanced data analytics,artificial intelligence-driven predictive algorithms,and closed-loop therapeutic systems.Additionally,the review addresses ongoing challenges in biomarker validation,sensor stability,user compliance,data privacy,and regulatory considerations.A holistic,multimodal approach enabled by these next-generation wearable biosensors holds significant potential for improving patient outcomes and facilitating proactive healthcare interventions in diabetes management.
基金funded by the National Natural Science Foundation of China(Grant Nos.62322410,52272168,624B2135,61804047)the Fundamental Research Funds for the Central Universities(No.WK2030000103)。
文摘Human action recognition(HAR)is crucial for the development of efficient computer vision,where bioinspired neuromorphic perception visual systems have emerged as a vital solution to address transmission bottlenecks across sensor-processor interfaces.However,the absence of interactions among versatile biomimicking functionalities within a single device,which was developed for specific vision tasks,restricts the computational capacity,practicality,and scalability of in-sensor vision computing.Here,we propose a bioinspired vision sensor composed of a Ga N/Al N-based ultrathin quantum-disks-in-nanowires(QD-NWs)array to mimic not only Parvo cells for high-contrast vision and Magno cells for dynamic vision in the human retina but also the synergistic activity between the two cells for in-sensor vision computing.By simply tuning the applied bias voltage on each QD-NW-array-based pixel,we achieve two biosimilar photoresponse characteristics with slow and fast reactions to light stimuli that enhance the in-sensor image quality and HAR efficiency,respectively.Strikingly,the interplay and synergistic interaction of the two photoresponse modes within a single device markedly increased the HAR recognition accuracy from 51.4%to 81.4%owing to the integrated artificial vision system.The demonstration of an intelligent vision sensor offers a promising device platform for the development of highly efficient HAR systems and future smart optoelectronics.
基金supported by the National Natural Science Foundation of China(NSFC 52175281,52475315)Youth Innovation Promotion Association of CAS(2021382)。
文摘The growing prevalence of exercise-induced tibial stress fractures demands wearable sensors capable of monitoring dynamic musculoskeletal loads with medical-grade precision.While flexible pressure-sensing insoles show clinical potential,their development has been hindered by the intrinsic trade-off between high sensitivity and full-range linearity(R^(2)>0.99 up to 1 MPa)in conventional designs.Inspired by the tactile sensing mechanism of human skin,where dermal stratification enables wide-range pressure adaptation and ion-channelregulated signaling maintains linear electrical responses,we developed a dual-mechanism flexible iontronic pressure sensor(FIPS).This innovative design synergistically combines two bioinspired components:interdigitated fabric microstructures enabling pressure-proportional contact area expansion(αP1/3)and iontronic film facilitating self-adaptive ion concentration modulation(αP^(2/3)),which together generate a linear capacitance-pressure response(CαP).The FIPS achieves breakthrough performance:242 kPa^(-1)sensitivity with 0.997linearity across 0-1 MPa,yielding a record linear sensing factor(LSF=242,000).The design is validated across various substrates and ionic materials,demonstrating its versatility.Finally,the FIPS-driven design enables a smart insole demonstrating 1.8%error in tibial load assessment during gait analysis,outperforming nonlinear counterparts(6.5%error)in early fracture-risk prediction.The biomimetic design framework establishes a universal approach for developing high-performance linear sensors,establishing generalized principles for medical-grade wearable devices.
基金The National Natural Science Foundation of China(No.51175267)the Natural Science Foundation of Jiangsu Province(No.BK2010481)+2 种基金the Ph.D.Programs Foundation of Ministry of Education of China(No.20113219120004)China Postdoctoral Science Foundation(No.20100481148)the Postdoctoral Science Foundation of Jiangsu Province(No.1001004B)
文摘To realize high-precision automatic measurement of two-dimensional geometric features on parts, a cooperative measurement system based on machine vision is constructed. Its hardware structure, functional composition and working principle are introduced. The mapping relationship between the feature image coordinates and the measuring space coordinates is established. The method of measuring path planning of small field of view （FOV） images is proposed. With the cooperation of the panoramic image of the object to be measured, the small FOV images with high object plane resolution are acquired automatically. Then, the auxiliary measuring characteristics are constructed and the parameters of the features to be measured are automatically extracted. Experimental results show that the absolute value of relative error is less than 0. 03% when applying the cooperative measurement system to gauge the hole distance of 100 mm nominal size. When the object plane resolving power of the small FOV images is 16 times that of the large FOV image, the measurement accuracy of small FOV images is improved by 14 times compared with the large FOV image. It is suitable for high-precision automatic measurement of two-dimensional complex geometric features distributed on large scale parts.
基金National Key Scientific Instrument and Equipment Development Project(No.2013YQ170539)
文摘Multi-sensor coordinate unification in dimensional metrology is used in order to get holistic, more accurate and reliable information about a workpiece based on several or multiple measurement values from one or more sensors. Because of the problem that standard ball is deficient as a standard artifact in the coordinate unification of high-precision composite measurement in two dimensions （2D） , a new method is proposed in this paper which uses angle gauge blocks as standard artifacts to achieve coordinate unification between the image sensor and the tactile probe. By comparing the standard ball with the angle gauge block as a standard artifact, theoretical analysis and experimental results are given to prove that it is more precise and more convenient to use angle gauge blocks as standard artifacts to achieve coordinate unification of high-precision composite measurement in two dimensions.
基金the National Natural Science Foundation of China(Grant No.42192535)the Open Fund of Wuhan,Gravitation and Solid Earth Tides,National Observation and Research Station(No.WHYWZ202204)+1 种基金the Strategic Pioneer Science and Technology Special Project of the Chinese Academy of Sciences(Grant No.XDB18010304)the National Natural Science Foundation of China(Grant No.41874096).
文摘The Tibetan Plateau(TP)is the youngest orogenic belt resulting from a continental collision on the Earth.It is a natural laboratory for studying continental dynamics,such as continental convergence,plate subduction,and plateau uplift.Investigating the deep structure of the TP has always been a popular issue in geological research.The Moho is the boundary between the crust and the mantle and therefore plays a crucial role in the Earth’s structure.Parameters such as depth and lateral variation,as well as the fine structure of the crust-mantle interface,reveal the lithospheric dynamics in the TP.Two methods are generally employed to study the Moho surface:seismic detection and gravity inversion.Seismic detection has the characteristic of high precision,but it is limited to a few cross-sectional lines and is quite costly.It is not suitable for and cannot be carried out over a large area of the TP.The Moho depth over a large area can be obtained through gravity inversion,but this method is affected by the nature of gravity data,and the accuracy of the inversion method is lower than that of seismic detection.In this work,a high-precision gravity field model was selected.The Parker-Oldenburg interface inversion method was used,within the constraints of seismic observations,and the Bott iteration method was introduced to enhance the inversion efficiency.The Moho depth in the TP was obtained with high precision,consistent with the seismic detection results.The research results showed that the shape of the Moho in the TP is complex and the variation range is large,reaching 60−80 km.In contrast with the adjacent area,a clear zone of sharp variation appears at the edge of the plateau.In the interior of the TP,the buried depth of the Moho is characterized by two depressions and two uplifts.To the south of the Yarlung Zangbo River,the Moho inclines to the north,and to the north,the Moho depresses downward,which was interpreted as the Indian plate subducting to the north below Xizang.The Moho depression on the north side of the Qiangtang block,reaching 72 km deep,may be a result of the southward subduction of the lithosphere.The Moho uplift of the Qiangtang block has the same strike as the Bangong−Nujiang suture zone,which may indicate that the area is compensated by a low-density and low-velocity mantle.
基金The work was supported by the National Natural Science Foundation of China(No.51874045)National Natural Science Foundation-Youth Foundation(52104056)+2 种基金Department of Natural Resources of Guangdong Province(GDNRC[2021]56)Postdoctoral innovative talents support program in China(BX2021374)Scientific Research Program of Hubei Provincial Department of Education(T2021004).
文摘A reliable multiphase flow simulator is an important tool to improve wellbore integrity and production decision-making.To develop a multiphase flow model with high adaptability and high accuracy,we first build a multiphase flow database with 3561 groups of data and developed a drift closure relationship with stable continuity and high adaptability.Second,a high-order numerical scheme with strong fault capture ability is constructed by effectively combining MUSCL technology,van Albada slope limiter and AUSMV numerical scheme.Finally,the energy equation is coupled into the AUSMV numerical scheme of the drift flow model in the form of finite difference.A transient non-isothermal wellbore multiphase flow model with wide applicability is formed by integrating the three technologies,and the effects of various factors on the calculation accuracy are studied.The accuracy of the simulator is verified by comparing the measurement results with the blowout experiment of a full-scale experimental well.
基金the National Natural Science Foundation of China(Grant Nos.11427803,11427901 and 11773040)the Strategic Pioneer Program on Space Science,Chinese Academy of Sciences(CAS)(XDA04061002 and XDA15010800)the Public Technology Service Center,National Astronomical Observatories of CAS(829011V01)。
文摘The magnetic field is one of the most important parameters in solar physics,and a polarimeter is the key device to measure the solar magnetic field.Liquid crystals based Stokes polarimeter is a novel technology,and will be applied for magnetic field measurement in the first space-based solar observatory satellite developed by China,Advanced Space-based Solar Observatory.However,the liquid crystals based Stokes polarimeter in space is not a mature technology.Therefore,it is of great scientific significance to study the control method and characteristics of the device.The retardation produced by a liquid crystal variable retarder is sensitive to the temperature,and the retardation changes 0.09°per 0.10℃.The error in polarization measurement caused by this change is 0.016,which affects the accuracy of magnetic field measurement.In order to ensure the stability of its performance,this paper proposes a high-precision temperature control system for liquid crystals based Stokes polarimeter in space.In order to optimize the structure design and temperature control system,the temperature field of liquid crystals based Stokes polarimeter is analyzed by the finite element method,and the influence of light on the temperature field of the liquid crystal variable retarder is analyzed theoretically.By analyzing the principle of highprecision temperature measurement in space,a high-precision temperature measurement circuit based on integrated operational amplifier,programmable amplifier and 12 bit A/D is designed,and a high-precision space temperature control system is developed by applying the integral separation PI temperature control algorithm and PWM driving heating films.The experimental results show that the effect of temperature control is accurate and stable,whenever the liquid crystals based Stokes polarimeter is either in the air or vacuum.The temperature stability is within±0.0150℃,which demonstrates greatly improved stability for the liquid crystals based Stokes polarimeter.
基金support from the National Natural Science Foundation of China(Nos.51775147 and 52005133).
文摘High-precision turning(HPT)is a main processing method for manufacturing rotary high-precision components,especially for metallic parts.However,the generated vibration between tool tip and workpiece during turning may seriously deteriorate the surface integrity.Therefore,exploring the effect of vibration on turning surface morphology and quality of copper parts using 3D surface topography regeneration model is crucial for predicting HPT performance.This developed model can update the machined surface topology in real time.In this study,the effects of tool arc radius,feed rate,radial vibration,axial vibration and tangential vibration on the surface topography and surface roughness were explored.The results show that the effect of radial vibration on surface topography is greater than that of axial vibration and tangential vibration.The radial vibration frequency is also critical.When vibration frequency changes,the surface topography profile presents three different types:the standard sinusoidal curve,the sinusoidal curve whose lowfrequency signal envelopes high-frequency signal,and the oscillation curve whose low-frequency signal superimposes high-frequency signal.In addition,HPT experiment was carried out to validate the developed model.The surface roughness obtained in the experiment was Ra=53 nm,while the roughness obtained by the simulation was Ra=46 nm,achieving a prediction accuracy of 86.7%.Received 4 September 2022;revised 3 October 2022;accepted 17 October 2022.
基金This work was supported by the National Meg-Science Engineering Project of the Chinese Government.
文摘This paper introduces a design of high-precision high-voltage fiber-optic analog sig-nal isolation converter based on the technology of Voltage-to-Frequency (V/F) and Frequency-to-Voltage (F/V) conversion. It describes the principle, system configuration and hardware design.
基金National Natural Science Foundation of China(U1764264/61873165).
文摘High-precision lane keeping is essential for the future autonomous driving.However,due to the imbalanced and inaccurate datasets collected by human drivers,current end-to-end driving models have poor lane keeping the effect.To improve the precision of lane keeping,this study presents a novel multi-state model-based end-to-end lane keeping method.First,three driving states will be defined:going straight,turning right and turning left.Second,the finite-state machine(FSM)table as well as three kinds of training datasets will be generated based on the three driving states.Instead of collecting the dataset by human drivers,the accurate dataset will be collected by the high-performance path following controller.Third,three sets of parameters based on 3DCNN-LSTM model will be trained for going straight,turning left and turning right,which will be combined with FSM table to form a multi-state model.This study evaluates the multi-state model by testing it on five tracks and recording the lane keeping error.The result shows the multi-state model-based end-to-end method performs the higher precision of lane keeping than the traditional single end-to-end model.
