Measurement precision of laser displacement sensor is subject to various factors,among which laser jitter and target tilt will directly lead to the position movement and shape variation of the laser spot,resulting in ...Measurement precision of laser displacement sensor is subject to various factors,among which laser jitter and target tilt will directly lead to the position movement and shape variation of the laser spot,resulting in displacement measurement errors,so that researchers have to do a lot of research on the spot centering algorithm to weaken the above effects,which can treat the symptoms but not the root cause.Starting from the source of the problem,this paper proposes a double focus double peak solution,which uses a reflector to change the direction of the optical path,so that the imaging spots of the designed two optical paths focus on the same CMOS,forming a double peak structure.When laser jitter or target tilt occurs,the center of the two laser spots is shifted,but they move in the same direction,while their relative position remains unchanged.Therefore,the displacement can be characterized by the relative position of the two laser spots,so that laser jitter and target tilt are suppressed from the source.However,the two spots imaged on CMOS form a non-Gaussian distributed double peak structure,so the conventional laser spot centering algorithms are no longer applicable.To this end,a double peak adaptive threshold waveform extraction method combined with grayscale gravity method is proposed for spot centering algorithm,which combines the suppression of laser jitter and target tilt from the source and the improvement of spot positioning precision which represents the displacement measurement precision,and is experimentally verified.展开更多
Monitoring biogenic amines,which are metabolic byproducts of shrimp spoilage,is crucial for assessing food quality.Currently,most detection methods for biogenic amines suffer from limitations such as time-consuming pr...Monitoring biogenic amines,which are metabolic byproducts of shrimp spoilage,is crucial for assessing food quality.Currently,most detection methods for biogenic amines suffer from limitations such as time-consuming procedures,complex operations,and delayed results.Colorimetric analysis techniques have gained attention in recent years due to their advantages of short analysis time,simple operation,and suitability for on-site testing.This study successfully developed a series of colorimetric sensor platforms for biogenic amines by loading the natural active ingredient curcumin(CUR)and its derivative of Boron complex BFCUR onto filter paper and electrospun nanofibre films(ENFs),respectively.By analyzing the color response differences of these sensors upon contact with biogenic amines,the colorimetric sensors with superior detection performance were selected and further applied to the visual monitoring and indication of shrimp spoilage processes.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
Developing effective,versatile,and high-precision sensing interfaces remains a crucial challenge in human-machine-environment interaction applications.Despite progress in interaction-oriented sensing skins,limitations...Developing effective,versatile,and high-precision sensing interfaces remains a crucial challenge in human-machine-environment interaction applications.Despite progress in interaction-oriented sensing skins,limitations remain in unit-level reconfiguration,multiaxial force and motion sensing,and robust operation across dynamically changing or irregular surfaces.Herein,we develop a reconfigurable omnidirectional triboelectric whisker sensor array(RO-TWSA)comprising multiple sensing units that integrate a triboelectric whisker structure(TWS)with an untethered hydro-sealing vacuum sucker(UHSVS),enabling reversibly portable deployment and omnidirectional perception across diverse surfaces.Using a simple dual-triangular electrode layout paired with MXene/silicone nanocomposite dielectric layer,the sensor unit achieves precise omnidirectional force and motion sensing with a detection threshold as low as 0.024 N and an angular resolution of 5°,while the UHSVS provides reliable and reversible multi-surface anchoring for the sensor units by involving a newly designed hydrogel combining high mechanical robustness and superior water absorption.Extensive experiments demonstrate the effectiveness of RO-TWSA across various interactive scenarios,including teleoperation,tactile diagnostics,and robotic autonomous exploration.Overall,RO-TWSA presents a versatile and high-resolution tactile interface,offering new avenues for intelligent perception and interaction in complex real-world environments.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
Fiber-structured ion sensors have gained traction in health monitoring and medical diagnostics owing to their structural flexibility,enhanced sensitivity,and suitability for integration into wearable devices.This stud...Fiber-structured ion sensors have gained traction in health monitoring and medical diagnostics owing to their structural flexibility,enhanced sensitivity,and suitability for integration into wearable devices.This study employed a simple and efficient solutionbased process to fabricate nanofibers containing aggregation-induced emission(AIE)dyes.The resulting AIE nanofibers exhibited stable and intense fluorescence,nanosecond fluorescence lifetime,and low-loss light transport when functioning as active waveguides.Additionally,crossed nanofiber intersections exhibited diffraction-limited emission spots.The AIE nanofibers demonstrate efficient and ionspecific fluorescence quenching in response to Ag^(+).These results support the development of sensing units capable of operating in liquid environments or in direct contact with skin or tissues,facilitating real-time monitoring of ion concentrations for personalized healthcare management.展开更多
The advancement of wearable sensing technologies demands multifunctional materials that integrate high sensitivity,environmental resilience,and intelligent signal processing.In this work,a flexible hydrophobic conduct...The advancement of wearable sensing technologies demands multifunctional materials that integrate high sensitivity,environmental resilience,and intelligent signal processing.In this work,a flexible hydrophobic conductive yarn(FCB@SY)featuring a controllable microcrack structure is developed via a synergistic approach combining ultrasonic swelling and non-solvent induced phase separation(NIPS).By embedding a robust conductive network and engineering microcrack morphology,the resulting sensor achieves an ultrahigh gauge factor(GF≈12,670),an ultrabroad working range(0%-547%),a low detection limit(0.5%),rapid response/recovery time(140 ms/140 ms),and outstanding durability over 10,000 cycles.Furthermore,the hydrophobic surface endowed by conductive coatings imparts exceptional chemical stability against acidic and alkaline environments,as well as reliable waterproof performance.This enables consistent functionality under harsh conditions,including underwater operation.Integrated with machine learning algorithms,the FCB@SY-based intelligent sensing system demonstrates dualmode capabilities in human motion tracking and gesture recognition,offering significant potential for applications in wearable electronics,human-machine interfaces,and soft robotics.展开更多
In the context of the rapid development of artificial intelligence and robotics,their application scenarios are continuously expanding to a variety of complex environments,with increasing attention being paid to the u...In the context of the rapid development of artificial intelligence and robotics,their application scenarios are continuously expanding to a variety of complex environments,with increasing attention being paid to the use of flexible sensors in lowtemperature environments.In this study,an ionic hydrogel was synthesized using acrylamide(AM),hydroxyethyl cellulose(HEC),and lithium chloride(LiCl)as composites.This hydrogel exhibits high adhesion,excellent sensitivity(gauge factor(GF)=2.84),rapid response time(100 ms),exceptional stretch ability(>1776%),high toughness(2.5 MJ/m^(3)),and the ability to maintain detectability at low temperatures(-60℃).HEC imparts reliable mechanical properties to the sensor through hydrogen bonding interactions of its hydroxyl groups.LiCl ensures that the sensor has outstanding antifreezing properties,maintains good conductivity and mechanical performance.Used for robotic attitude detection,the sensor demonstrated accurate recognition of various joint movements at both 20 and -20℃.This technology was extended to industrial operations and maintenance,where a mechanical claw was used to grasp parts at both room temperature and low temperature.A convolutional neural network deep learning algorithm was employed to identify and classify eight types of parts,achieving an impressive recognition accuracy of 98.8%.The polyacrylamide(PAM)/HEC/LiCl hydrogel sensor demonstrates the capability for wide-temperature range detection in flexible robotics,holding significant potential for future applications in human-machine interaction,tactile perception,and related fields.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
A grating eddy current displacement sensor(GECDS) can be used in a watertight electronic transducer to realize long range displacement or position measurement with high accuracy in difficult industry conditions.The pa...A grating eddy current displacement sensor(GECDS) can be used in a watertight electronic transducer to realize long range displacement or position measurement with high accuracy in difficult industry conditions.The parameters optimization of the sensor is essential for economic and efficient production.This paper proposes a method to combine an artificial neural network(ANN) and a genetic algorithm(GA) for the sensor parameters optimization.A neural network model is developed to map the complex relationship between design parameters and the nonlinearity error of the GECDS,and then a GA is used in the optimization process to determine the design parameter values,resulting in a desired minimal nonlinearity error of about 0.11%.The calculated nonlinearity error is 0.25%.These results show that the proposed method performs well for the parameters optimization of the GECDS.展开更多
The grating eddy current displacement sensor (GECDS) for distance or position measurement used in watertight electronic calipers was described. The sensor relies on repetitive variation of inductance against displacem...The grating eddy current displacement sensor (GECDS) for distance or position measurement used in watertight electronic calipers was described. The sensor relies on repetitive variation of inductance against displacement caused by the change of coupling areas between moving coils and static reflectors. The investigations focused on setting up and utilizing a computer model of the 3D eddy current fields and geometry to analyze causes of the production of measurement blind areas, and to investigate effects of the sensor parameters, such as axial gap between coils and reflectors, reflector length and reflector width on characteristics of the sensor. Simulation results indicated that the sensor has the smallest nonlinearity error of 0.15%, which agrees well with the experimental results.展开更多
A high temperature displacement sensor based on the principle of eddy-current is investigated. A new temperature compensation technique by using eddy-current effect is presented to satisfy the special requirement at h...A high temperature displacement sensor based on the principle of eddy-current is investigated. A new temperature compensation technique by using eddy-current effect is presented to satisfy the special requirement at high temperature up to 550℃. The experiment shows that the temperature compensation technique leads to good temperature stability for the sensors. The variation of the sensitivity as well as the temperature drift of the sensor with temperature compensation technique is only about 7.4% and 90-350 mV at 550 ℃ compared with that at room temperature, and that of the sensor without temperature compensation technique is about 31.2% and 2-3 V at 550 ℃ compared with that at room temperature. A new dynamic calibration method for the eddy-current displacement sensor is presented, which is very easy to be realized especially in high frequency and at high temperatures. The high temperature displacement sensors developed are successfully used at temperature up to 550 ℃ in a magnetic bearing system for more than 100 h.展开更多
In order to implement 3D scanning of those complicated parts such as blades in the aviation field,a non-contact optical measuring system is established in the paper,which integrates a laser displacement sensor,a probe...In order to implement 3D scanning of those complicated parts such as blades in the aviation field,a non-contact optical measuring system is established in the paper,which integrates a laser displacement sensor,a probe head,the frame of a coordinate measuring machine（CMM）,etc.As the output of the laser sensor directly obtained possesses the 1D length of the laser beam,it needs to determine the unit direction vector of the laser beam denoted as（l,m,n）by calibration so as to convert the 1D values into 3D coordinates of target points.Therefore,an extrinsic calibration method based on a standard sphere is proposed to accomplish this task in the paper.During the calibration procedure,the laser sensor moves along with the motion of the CMM and gathers the required data on the spherical surface.Then,both the output of the laser sensor and the grating readings of the CMM are substituted into the constraint equation of the spherical surface,in which an over-determined nonlinear equation group containing unknown parameters is established.For the purpose of solving the equation group,a method based on non-linear least squares optimization is put forward.Finally,the system after calibration is utilized to measure the diameter of a metallic sphere 10 times from different orientations to verify the calibration accuracy.In the experiment,the errors between the measured results and the true values are all smaller than 0.03 mm,which manifests the validity and practicality of the extrinsic calibration method presented in the paper.展开更多
An on-machine measuring(OMM)system with a laser displacement sensor(LDS)is designed for measuring free-form surfaces of hypersonic aircraft’s radomes.To improve the measurement accuracy of the OMM system,a novel Iter...An on-machine measuring(OMM)system with a laser displacement sensor(LDS)is designed for measuring free-form surfaces of hypersonic aircraft’s radomes.To improve the measurement accuracy of the OMM system,a novel Iteratively Automatic machine learning Boosted hand-eye Calibration(IABC)method is proposed.Both the hand-eye relationship and LDS measurement errors can be calibrated in one calibration process without any hardware changes via IABC.Firstly,a new objective function is derived,containing analytical parameters of the handeye relationship and LDS errors.Then,a hybrid calibration model composed of two kernels is proposed to solve the objective function.One kernel is the analytical kernel designed for solving analytical parameters.Another kernel is the automatic machine learning(AutoML)kernel designed to model LDS errors.The two kernels are connected with stepwise iterations to find the best calibration results.Compared with traditional methods,hand-eye experiments show that IABC reduces the calibration RMSE by about 50%.Verification experiments show that IABC reduces the measurement deviations by about 25%-50%and RMSEs within 40%.Even when the training data are obviously less than the test data,IABC performs well.Experiments demonstrate that IABC is more accurate than traditional hand-eye methods.展开更多
A model of correcting the nonlinear error of photoelectric displacement sensor was established based on the least square support vector machine.The parameters of the correcting nonlinear model,such as penalty factor a...A model of correcting the nonlinear error of photoelectric displacement sensor was established based on the least square support vector machine.The parameters of the correcting nonlinear model,such as penalty factor and kernel parameter,were optimized by chaos genetic algorithm.And the nonlinear correction of photoelectric displacement sensor based on least square support vector machine was applied.The application results reveal that error of photoelectric displacement sensor is less than 1.5%,which is rather satisfactory for nonlinear correction of photoelectric displacement sensor.展开更多
Railway turnout contact monitoring is very important in high-speed rail operation systems. In order to measure the distance between the sharp rail and the basic rail in a switch system, a wide-range, high-precision fi...Railway turnout contact monitoring is very important in high-speed rail operation systems. In order to measure the distance between the sharp rail and the basic rail in a switch system, a wide-range, high-precision fiber Bragg grating(FBG) displacement sensor was designed. Because the distance between the sharp and basic rails is always greater than 14 cm, the measurement range width and accuracy of the proposed sensor system are ensured through the use of a long spring and a beam of constant strength. A differential compensation method is used to eliminate temperature effects. Test results show that the resolution of the proposed sensor is 0.040 mm and the measuring range is 0—170 mm. A field test was also carried out to evaluate the performance of the sensors.展开更多
By accurately measuring the displacement between the roller surface and the optical fiber probe relative to a null position, we can test the roller wear. The whole testing method and system were introduced. Each part ...By accurately measuring the displacement between the roller surface and the optical fiber probe relative to a null position, we can test the roller wear. The whole testing method and system were introduced. Each part of the testing system was illustrated. And also a novel fiber-optic sensor with three probes in equal transverse space is adopted. Using this sensor, the effects of fluctuations in the light source, reflectivity changing of target surface and the intensity losses in the fiber lines are automatically compensated. This method offers such advantages as non-contact, no electromagnetic interference, simplicity, low cost, high sensitivity, good accuracy and stability.展开更多
基金the Biomedical Science and Technology Support Special Project of Shanghai Science and Technology Committee(No.20S31908300)。
文摘Measurement precision of laser displacement sensor is subject to various factors,among which laser jitter and target tilt will directly lead to the position movement and shape variation of the laser spot,resulting in displacement measurement errors,so that researchers have to do a lot of research on the spot centering algorithm to weaken the above effects,which can treat the symptoms but not the root cause.Starting from the source of the problem,this paper proposes a double focus double peak solution,which uses a reflector to change the direction of the optical path,so that the imaging spots of the designed two optical paths focus on the same CMOS,forming a double peak structure.When laser jitter or target tilt occurs,the center of the two laser spots is shifted,but they move in the same direction,while their relative position remains unchanged.Therefore,the displacement can be characterized by the relative position of the two laser spots,so that laser jitter and target tilt are suppressed from the source.However,the two spots imaged on CMOS form a non-Gaussian distributed double peak structure,so the conventional laser spot centering algorithms are no longer applicable.To this end,a double peak adaptive threshold waveform extraction method combined with grayscale gravity method is proposed for spot centering algorithm,which combines the suppression of laser jitter and target tilt from the source and the improvement of spot positioning precision which represents the displacement measurement precision,and is experimentally verified.
基金Supported by the Guangdong-Hong Kong-Macao Joint Laboratory on Micro-Nano Manufacturing Technology,China(No.2021LSYS004)Guangdong Provincial Key Laboratory of Sustainable Biomimetic Materials and Green Energy,China(No.2024B1212010003)。
文摘Monitoring biogenic amines,which are metabolic byproducts of shrimp spoilage,is crucial for assessing food quality.Currently,most detection methods for biogenic amines suffer from limitations such as time-consuming procedures,complex operations,and delayed results.Colorimetric analysis techniques have gained attention in recent years due to their advantages of short analysis time,simple operation,and suitability for on-site testing.This study successfully developed a series of colorimetric sensor platforms for biogenic amines by loading the natural active ingredient curcumin(CUR)and its derivative of Boron complex BFCUR onto filter paper and electrospun nanofibre films(ENFs),respectively.By analyzing the color response differences of these sensors upon contact with biogenic amines,the colorimetric sensors with superior detection performance were selected and further applied to the visual monitoring and indication of shrimp spoilage processes.
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 National Natural Science Foundation of China(General Program)under Grant 52571385National Key R&D Program of China(Grant No.2024YFC2815000 and No.2024YFB3816000)+12 种基金Open Fund of State Key Laboratory of Deep-sea Manned Vehicles(Grant No.2025SKLDMV07)Shenzhen Science and Technology Program(WDZC20231128114452001,JCYJ20240813112107010 and JCYJ20240813111910014)the Tsinghua SIGS Scientific Research Startup Fund(QD2022021C)the Dreams Foundation of Jianghuai Advance Technology Center(2023-ZM 01 Z006)the Ocean Decade International Cooperation Center(ODCC)(GHZZ3702840002024020000026)Shenzhen Key Laboratory of Advanced Technology for Marine Ecology(ZDSYS20230626091459009)Shenzhen Science and Technology Program(No.KJZD20240903100905008)the National Natural Science Foundation of China(No.22305141)Pearl River Talent Program(No.2023QN10C114)General Program of Guangdong Province(No.2025A1515011700)the Guangdong Innovative and Entrepreneurial Research Team Program(2023ZT10C040)Scientific Research Foundation from Shenzhen Finance Bureau(No.GJHZ20240218113600002)Tsinghua University(JC2023001).
文摘Developing effective,versatile,and high-precision sensing interfaces remains a crucial challenge in human-machine-environment interaction applications.Despite progress in interaction-oriented sensing skins,limitations remain in unit-level reconfiguration,multiaxial force and motion sensing,and robust operation across dynamically changing or irregular surfaces.Herein,we develop a reconfigurable omnidirectional triboelectric whisker sensor array(RO-TWSA)comprising multiple sensing units that integrate a triboelectric whisker structure(TWS)with an untethered hydro-sealing vacuum sucker(UHSVS),enabling reversibly portable deployment and omnidirectional perception across diverse surfaces.Using a simple dual-triangular electrode layout paired with MXene/silicone nanocomposite dielectric layer,the sensor unit achieves precise omnidirectional force and motion sensing with a detection threshold as low as 0.024 N and an angular resolution of 5°,while the UHSVS provides reliable and reversible multi-surface anchoring for the sensor units by involving a newly designed hydrogel combining high mechanical robustness and superior water absorption.Extensive experiments demonstrate the effectiveness of RO-TWSA across various interactive scenarios,including teleoperation,tactile diagnostics,and robotic autonomous exploration.Overall,RO-TWSA presents a versatile and high-resolution tactile interface,offering new avenues for intelligent perception and interaction in complex real-world environments.
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.
基金partially supported by the National Natural Science Foundation of China(Nos.11804120,61827822,and 22275072)Guangdong Basic and Applied Basic Research Foundation(No.2023A1515030209)+1 种基金Research Projects from Guangzhou(Nos.2023A03J0018 and 2024A04J3712)Fundamental Research Funds for the Central Universities(No.21623412).
文摘Fiber-structured ion sensors have gained traction in health monitoring and medical diagnostics owing to their structural flexibility,enhanced sensitivity,and suitability for integration into wearable devices.This study employed a simple and efficient solutionbased process to fabricate nanofibers containing aggregation-induced emission(AIE)dyes.The resulting AIE nanofibers exhibited stable and intense fluorescence,nanosecond fluorescence lifetime,and low-loss light transport when functioning as active waveguides.Additionally,crossed nanofiber intersections exhibited diffraction-limited emission spots.The AIE nanofibers demonstrate efficient and ionspecific fluorescence quenching in response to Ag^(+).These results support the development of sensing units capable of operating in liquid environments or in direct contact with skin or tissues,facilitating real-time monitoring of ion concentrations for personalized healthcare management.
基金the financial support of this work by the National Natural Science Foundation of China(No.52373093)Excellent Youth Found of Natural Science Foundation of Henan Province(No.242300421062)+1 种基金Central Plains Youth Top notch Talent Program of Henan Provincethe 111 project(No.D18023).
文摘The advancement of wearable sensing technologies demands multifunctional materials that integrate high sensitivity,environmental resilience,and intelligent signal processing.In this work,a flexible hydrophobic conductive yarn(FCB@SY)featuring a controllable microcrack structure is developed via a synergistic approach combining ultrasonic swelling and non-solvent induced phase separation(NIPS).By embedding a robust conductive network and engineering microcrack morphology,the resulting sensor achieves an ultrahigh gauge factor(GF≈12,670),an ultrabroad working range(0%-547%),a low detection limit(0.5%),rapid response/recovery time(140 ms/140 ms),and outstanding durability over 10,000 cycles.Furthermore,the hydrophobic surface endowed by conductive coatings imparts exceptional chemical stability against acidic and alkaline environments,as well as reliable waterproof performance.This enables consistent functionality under harsh conditions,including underwater operation.Integrated with machine learning algorithms,the FCB@SY-based intelligent sensing system demonstrates dualmode capabilities in human motion tracking and gesture recognition,offering significant potential for applications in wearable electronics,human-machine interfaces,and soft robotics.
基金supported by the National Natural Science Foundation of China(No.52475580)the Special Foundation of the Taishan Scholar Project(No.tsqn202211077)+3 种基金the Shandong Provincial Natural Science Foundation(No.ZR2023ME118)the Open Project of State Key Laboratory of Chemical Safety(No.SKLCS-2024020)the Fundamental Research Funds for the Central Universities(No.24CX02014A)the Fund of State Key Laboratory of Deep Oil and Gas,China University of Petroleum(East China).
文摘In the context of the rapid development of artificial intelligence and robotics,their application scenarios are continuously expanding to a variety of complex environments,with increasing attention being paid to the use of flexible sensors in lowtemperature environments.In this study,an ionic hydrogel was synthesized using acrylamide(AM),hydroxyethyl cellulose(HEC),and lithium chloride(LiCl)as composites.This hydrogel exhibits high adhesion,excellent sensitivity(gauge factor(GF)=2.84),rapid response time(100 ms),exceptional stretch ability(>1776%),high toughness(2.5 MJ/m^(3)),and the ability to maintain detectability at low temperatures(-60℃).HEC imparts reliable mechanical properties to the sensor through hydrogen bonding interactions of its hydroxyl groups.LiCl ensures that the sensor has outstanding antifreezing properties,maintains good conductivity and mechanical performance.Used for robotic attitude detection,the sensor demonstrated accurate recognition of various joint movements at both 20 and -20℃.This technology was extended to industrial operations and maintenance,where a mechanical claw was used to grasp parts at both room temperature and low temperature.A convolutional neural network deep learning algorithm was employed to identify and classify eight types of parts,achieving an impressive recognition accuracy of 98.8%.The polyacrylamide(PAM)/HEC/LiCl hydrogel sensor demonstrates the capability for wide-temperature range detection in flexible robotics,holding significant potential for future applications in human-machine interaction,tactile perception,and related fields.
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.
文摘A grating eddy current displacement sensor(GECDS) can be used in a watertight electronic transducer to realize long range displacement or position measurement with high accuracy in difficult industry conditions.The parameters optimization of the sensor is essential for economic and efficient production.This paper proposes a method to combine an artificial neural network(ANN) and a genetic algorithm(GA) for the sensor parameters optimization.A neural network model is developed to map the complex relationship between design parameters and the nonlinearity error of the GECDS,and then a GA is used in the optimization process to determine the design parameter values,resulting in a desired minimal nonlinearity error of about 0.11%.The calculated nonlinearity error is 0.25%.These results show that the proposed method performs well for the parameters optimization of the GECDS.
文摘The grating eddy current displacement sensor (GECDS) for distance or position measurement used in watertight electronic calipers was described. The sensor relies on repetitive variation of inductance against displacement caused by the change of coupling areas between moving coils and static reflectors. The investigations focused on setting up and utilizing a computer model of the 3D eddy current fields and geometry to analyze causes of the production of measurement blind areas, and to investigate effects of the sensor parameters, such as axial gap between coils and reflectors, reflector length and reflector width on characteristics of the sensor. Simulation results indicated that the sensor has the smallest nonlinearity error of 0.15%, which agrees well with the experimental results.
基金This project is supported by European Community Project, National NaturalScience Foundation of China (No.50437010) and Aviation Science Founda-tion of China (No.99C52072).
文摘A high temperature displacement sensor based on the principle of eddy-current is investigated. A new temperature compensation technique by using eddy-current effect is presented to satisfy the special requirement at high temperature up to 550℃. The experiment shows that the temperature compensation technique leads to good temperature stability for the sensors. The variation of the sensitivity as well as the temperature drift of the sensor with temperature compensation technique is only about 7.4% and 90-350 mV at 550 ℃ compared with that at room temperature, and that of the sensor without temperature compensation technique is about 31.2% and 2-3 V at 550 ℃ compared with that at room temperature. A new dynamic calibration method for the eddy-current displacement sensor is presented, which is very easy to be realized especially in high frequency and at high temperatures. The high temperature displacement sensors developed are successfully used at temperature up to 550 ℃ in a magnetic bearing system for more than 100 h.
基金supported by the National Science and Technology Major Project for ‘‘High-grade Numerical Control Machine Tools and Basic Manufacturing Equipment” of China (No. 2013ZX04001071)
文摘In order to implement 3D scanning of those complicated parts such as blades in the aviation field,a non-contact optical measuring system is established in the paper,which integrates a laser displacement sensor,a probe head,the frame of a coordinate measuring machine（CMM）,etc.As the output of the laser sensor directly obtained possesses the 1D length of the laser beam,it needs to determine the unit direction vector of the laser beam denoted as（l,m,n）by calibration so as to convert the 1D values into 3D coordinates of target points.Therefore,an extrinsic calibration method based on a standard sphere is proposed to accomplish this task in the paper.During the calibration procedure,the laser sensor moves along with the motion of the CMM and gathers the required data on the spherical surface.Then,both the output of the laser sensor and the grating readings of the CMM are substituted into the constraint equation of the spherical surface,in which an over-determined nonlinear equation group containing unknown parameters is established.For the purpose of solving the equation group,a method based on non-linear least squares optimization is put forward.Finally,the system after calibration is utilized to measure the diameter of a metallic sphere 10 times from different orientations to verify the calibration accuracy.In the experiment,the errors between the measured results and the true values are all smaller than 0.03 mm,which manifests the validity and practicality of the extrinsic calibration method presented in the paper.
基金supported by the National Natural Science Foundation of China (Nos. 51875406 and 51805365)
文摘An on-machine measuring(OMM)system with a laser displacement sensor(LDS)is designed for measuring free-form surfaces of hypersonic aircraft’s radomes.To improve the measurement accuracy of the OMM system,a novel Iteratively Automatic machine learning Boosted hand-eye Calibration(IABC)method is proposed.Both the hand-eye relationship and LDS measurement errors can be calibrated in one calibration process without any hardware changes via IABC.Firstly,a new objective function is derived,containing analytical parameters of the handeye relationship and LDS errors.Then,a hybrid calibration model composed of two kernels is proposed to solve the objective function.One kernel is the analytical kernel designed for solving analytical parameters.Another kernel is the automatic machine learning(AutoML)kernel designed to model LDS errors.The two kernels are connected with stepwise iterations to find the best calibration results.Compared with traditional methods,hand-eye experiments show that IABC reduces the calibration RMSE by about 50%.Verification experiments show that IABC reduces the measurement deviations by about 25%-50%and RMSEs within 40%.Even when the training data are obviously less than the test data,IABC performs well.Experiments demonstrate that IABC is more accurate than traditional hand-eye methods.
基金Project(50925727) supported by the National Fund for Distinguish Young Scholars of ChinaProject(60876022) supported by the National Natural Science Foundation of China+1 种基金Project(2010FJ4141) supported by Hunan Provincial Science and Technology Foundation,ChinaProject supported by the Fund of the Key Construction Academic Subject (Optics) of Hunan Province,China
文摘A model of correcting the nonlinear error of photoelectric displacement sensor was established based on the least square support vector machine.The parameters of the correcting nonlinear model,such as penalty factor and kernel parameter,were optimized by chaos genetic algorithm.And the nonlinear correction of photoelectric displacement sensor based on least square support vector machine was applied.The application results reveal that error of photoelectric displacement sensor is less than 1.5%,which is rather satisfactory for nonlinear correction of photoelectric displacement sensor.
基金supported by the National Natural Science Foundation of China(Nos.51578349 and 51608336)the China Postdoctoral Science Foundation(No.2017M610170)
文摘Railway turnout contact monitoring is very important in high-speed rail operation systems. In order to measure the distance between the sharp rail and the basic rail in a switch system, a wide-range, high-precision fiber Bragg grating(FBG) displacement sensor was designed. Because the distance between the sharp and basic rails is always greater than 14 cm, the measurement range width and accuracy of the proposed sensor system are ensured through the use of a long spring and a beam of constant strength. A differential compensation method is used to eliminate temperature effects. Test results show that the resolution of the proposed sensor is 0.040 mm and the measuring range is 0—170 mm. A field test was also carried out to evaluate the performance of the sensors.
文摘By accurately measuring the displacement between the roller surface and the optical fiber probe relative to a null position, we can test the roller wear. The whole testing method and system were introduced. Each part of the testing system was illustrated. And also a novel fiber-optic sensor with three probes in equal transverse space is adopted. Using this sensor, the effects of fluctuations in the light source, reflectivity changing of target surface and the intensity losses in the fiber lines are automatically compensated. This method offers such advantages as non-contact, no electromagnetic interference, simplicity, low cost, high sensitivity, good accuracy and stability.
