Severe acute pancreatitis(SAP)can induce acute respiratory distress syndrome(ARDS)and abdominal compartment syndrome(ACS).Although prone position ventilation(PPV)can improve outcomes in patients with ARDS,there is sig...Severe acute pancreatitis(SAP)can induce acute respiratory distress syndrome(ARDS)and abdominal compartment syndrome(ACS).Although prone position ventilation(PPV)can improve outcomes in patients with ARDS,there is significant controversy regarding its concurrent use with ACS owing to concerns of increased risk of intra-abdominal pressure(IAP).[1]We present a case of successful PPV application without adverse eff ects.展开更多
Background:Pressure injury(PI)is a prevalent complication in pediatric cardiac surgery,with higher incidence than in general pediatric populations due to children’s thin skin,underdeveloped subcutaneous tissue,and pr...Background:Pressure injury(PI)is a prevalent complication in pediatric cardiac surgery,with higher incidence than in general pediatric populations due to children’s thin skin,underdeveloped subcutaneous tissue,and prolonged intraoperative pressure.Objective:To evaluate the effectiveness of the curvilinear supine position(CSP)in preventing PI among children undergoing congenital heart disease(CHD)surgery.Methods:Between October 2024 and February 2025,a single-center randomized controlled trial was conducted.Of the 80 children initially enrolled for congenital heart disease(CHD)surgery,77(aged 1 month to 14 years)completed the study and were included in the final analysis after 3 were excluded due to protocol violations.Participants were randomly assigned to the CSP group(n=38)or the conventional supine position group(n=39).Results:The incidence of PI was significantly lower in the CSP group(2.6%)compared to the control group(20.5%)(p=0.029).Postoperative LDH levels were also significantly reduced in the CSP group(422.67±86.52 U/L vs.592.92±215.71 U/L;p=0.031),while preoperative LDH and surgical variables(e.g.,cardiopulmonary bypass time)were comparable between groups.Although the CSP group had a shorter hospital stay(17.24 vs.22.51 days),the difference was not statistically significant(p=0.085).Caregiver satisfaction was significantly higher in the CSP group(100.0%vs.84.6%;p=0.025).Conclusion:CSP effectively reduces PI incidence,mitigates tissue injury,and enhances caregiver satisfaction in pediatric cardiac surgery,offering a safe and feasible strategy for perioperative PI prevention.展开更多
The high-quality assembly of Large Aircraft Components(LACs)is essential in modern aviation manufacturing.Numerical control locators are employed for the posture adjustment of LAC,yet the system's multi-input mult...The high-quality assembly of Large Aircraft Components(LACs)is essential in modern aviation manufacturing.Numerical control locators are employed for the posture adjustment of LAC,yet the system's multi-input multi-output,nonlinearity,and strong coupling presents significant challenges.The substantial internal force generated during the adjustment process can potentially damage the LAC and degrade the assembly quality.Hence,a workspace-based hybrid force position control scheme was developed to achieve high quality assembly with high-precision and lower internal force.Firstly,an offline workspace analysis with inherent geometric characteristics to form time-varying posture error constraint.Then,the posture error is integrated into the online position axis control to ensure tracking the ideal posture,while the force control axis compensates for posture deviation by minimizing internal force,thereby achieving high precision and low internal force.Finally,the effectiveness was demonstrated through experiments.The root mean square errors of orientation and position are 104 rad and 0.1 mm,respectively.A reduction in internal force can range from 10.96%to 57.4%compared to the traditional method.Key points'max position error is decreased from 0.32 mm to 0.18 mm,satisfying the 0.5 mm tolerance.Therefore,the proposed method will help promote the development of high-performance manufacturing.展开更多
The fluorination strategy has been proven effective in significantly enhancing the photovoltaic performance of organic solar cells(OSCs) based on non-fused ring electron acceptors(NFREAs).However,research on the impac...The fluorination strategy has been proven effective in significantly enhancing the photovoltaic performance of organic solar cells(OSCs) based on non-fused ring electron acceptors(NFREAs).However,research on the impact of fluorination positions at side chains on NFREAs device performance remains scant.In this study,we introduce two isomeric NFREAs,designated as GA-2F-E and GA-2F,distinguished by their fluorination positions at the side chains.Both NFREAs share a thiophene[3,2-b]thiophene core,but their side chains differ:GA-2F-E features two(4-butylphenyl)-N-(4-fluorophenyl) amino groups,whereas GA-2F's side chains consist of bis(4-fluorophenyl)amino and bis(4-butylphenyl)amino groups attached to opposite sides of the core.To delve into the influence of fluorination positions on the optoelectronic properties,aggregation behavior,and overall efficiency of the acceptor molecules,a comprehensive investigation was conducted.The findings reveal that,despite similar photophysical properties and comparable absorption bandwidths,GA-2F-E,with fluorine atoms positioned on both sides of the molecular framework,demonstrates more compact π-π stacking,reduced bimolecular recombination,superior exciton transport,and a more balanced,higher mobility.As a result of these advantages,OSCs optimized with D18:GA-2F-E achieve a remarkable power conversion efficiency(PCE) of 16.45 %,surpassing the 15.83 %PCE of devices utilizing D18:GA-2F.This research underscores the potential of NFREAs in future applications and highlights the significance of fluorination positions in enhancing OSC performance,paving the way for the development of more efficient NFREAs.展开更多
AIM:To evaluate and compare alterations in the effective lens position(ELP)and refractive outcomes among three distinct intraocular lens(IOL)types.METHODS:Patients with cataracts were enrolled and allocated to 3 group...AIM:To evaluate and compare alterations in the effective lens position(ELP)and refractive outcomes among three distinct intraocular lens(IOL)types.METHODS:Patients with cataracts were enrolled and allocated to 3 groups:Group A(implanted with the SN6CWS),Group B(implanted with the MI60),and Group C(implanted with the Aspira-aA).ELP measurements were obtained with swept-source optical coherence tomography(SS-OCT)at 1d,1wk,1mo,and 3mo postoperatively.Subjective refraction assessments were conducted at 1wk,1mo,and 3mo following surgery.RESULTS:The study included 189 eyes of 150 cataract patients(66 males).There were 77 eyes in Group A,55 eyes in Group B,and 57 eyes in Group C.The root mean square of the ELP(ELPRMS)within the initial 3mo was significantly lower for Group A than for Groups B and C.Refractive changes within Group A were not significant across the time points of 1wk,1mo,and 3mo.Conversely,both Group B and Group C demonstrated statistically significant shifts toward hyperopia from 1wk to 3mo postsurgery.CONCLUSION:Among the three IOLs examined,the SN6CWS IOL showes the greatest stability during the first 3mo postoperatively.Between 1wk and 3mo after surgery,notable hyperopic shifts are evident in eyes implanted with the MI60 and Aspira-aA IOLs,whereas refractive outcomes remain relatively constant in eyes implanted with SN6CWS IOLs.展开更多
Rotating Single-Baseline Interferometer(RSBI)systems have attracted considerable attention for Direct Position Determination(DPD)due to their simplicity and high localization accuracy.Nevertheless,the growing complexi...Rotating Single-Baseline Interferometer(RSBI)systems have attracted considerable attention for Direct Position Determination(DPD)due to their simplicity and high localization accuracy.Nevertheless,the growing complexity of electromagnetic environments has led to scenarios with multiple time-frequency aliased sources,rendering conventional DPD methods for RSBI systems ineffective.Previous studies have predominantly concentrated on deploying antenna arrays and applying related signal-processing techniques for localization.Typically,these approaches necessitate that the number of physical antennas exceeds the number of sources.For RSBI systems already in practical operation,this would entail the installation of additional physical antennas,which implies equipment recycling and hardware upgrades.In numerous cases,such modifications are unfeasible.This paper proposes a novel Relative Offset-based Direct Position Determination(RO-DPD)method for RSBI systems that can handle multiple time-frequency aliased sources.The proposed method overcomes the challenge of simultaneous positioning without requiring hardware modifications by leveraging time accumulation and algorithmic enhancements.The implementation of the method involves three key steps.Firstly,the rotation of the interferometer is synthesized into a virtual Uniform Circular Array(UCA).Secondly,a novel estimation variable,termed relative offset,is introduced.The variable serves as an intermediate parameter to establish correlation equations between the positions of multiple time-frequency aliased sources and the intercepted signals.Thirdly,the relative offset model in the UCA is transformed into a virtual Uniform Linear Array(ULA)model,from which the cost function can be derived via the Spatial Smoothing(SS)MUSIC algorithm.Theoretical analysis and simulation results verify the effectiveness of the proposed method.Compared with traditional approaches,the RO-DPD method maintains the low complexity of RSBI systems while demonstrating robust performance in complex electromagnetic environments.展开更多
In position-sensorless brushless direct current(DC)motors(BLDCMs)fed by a four-switch three-phase(FSTP)inverter,only two phases are fully controlled,while the remaining phase is tied to the midpoint of the split DC-li...In position-sensorless brushless direct current(DC)motors(BLDCMs)fed by a four-switch three-phase(FSTP)inverter,only two phases are fully controlled,while the remaining phase is tied to the midpoint of the split DC-link capacitors.The voltage pulses required by inductance-based initial position detection can cause unequal discharge of the series capacitors,shifting the neutral-point voltage away from half of DC-link voltage(U_(dc)/2).This neutral-point drift breaks the spatial symmetry of the inverter voltage vectors,so the 360°electrical period can no longer be evenly partitioned into six sectors during initial rotor position detection.To address this issue,this paper proposes a detection-pulse injection sequence that explicitly accounts for the asymmetric voltage vectors of the FSTP inverter.With the proposed sequence,the initial rotor position can be identified within a 30°electrical sector.The method requires no additional voltage or current sensors,and experimental results confirm its feasibility.展开更多
Deep learning has been recognized as an effective method for indoor positioning.However,most existing real-valued neural networks(RVNNs)treat the two constituent components of complex-valued channel state information(...Deep learning has been recognized as an effective method for indoor positioning.However,most existing real-valued neural networks(RVNNs)treat the two constituent components of complex-valued channel state information(CSI)as real-valued inputs,potentially discarding useful information embedded in the original CSI.In addition,existing positioning models generally face the contradiction between computational complexity and positioning accuracy.To address these issues,we combine graph neural network(GNN)with complex-valued neural network(CVNN)to construct a lightweight indoor positioning model named CGNet.CGNet employs complexvalued convolution operation to directly process the original CSI data,fully exploiting the correlation between real and imaginary parts of CSI while extracting local features.Subsequently,the feature values are treated as nodes,and conditional position encoding(CPE)module is applied to add positional information.To reduce the number of connections in the graph structure and lower themodel complexity,feature information is mapped to an efficient graph structure through a dynamic axial graph construction(DAGC)method,with global features extracted usingmaximum relative graph convolution(MRConv).Experimental results show that,on the CTW dataset,CGNet achieves a 10%improvement in positioning accuracy compared to existing methods,while the number of model parameters is only 0.8 M.CGNet achieves excellent positioning accuracy with very few parameters.展开更多
Modular truss space deployable antennas are key for future large aperture,high precision antennas,already proven in various in-orbit applications globally.This paper introduces a design method for a tetrahedral basic ...Modular truss space deployable antennas are key for future large aperture,high precision antennas,already proven in various in-orbit applications globally.This paper introduces a design method for a tetrahedral basic unit mechanism with dual height positioning nodes.A parametric model is established,and its DOF are analyzed to confirm the mechanism's validity.The new tetrahedral basic unit mechanism constructed by this method is a single DOF mechanism and can locate different parabolic node heights.In order to further adapt to the parabolic and large aperture requirements of the deployable antenna of the truss,a combination unit and modular unit mechanism are developed based on this tetrahedral unit.The DOF and deployment characteristics of the modular unit mechanism are analyzed and validated through simulations.Various networking methods for the modular units are proposed,followed by a comprehensive performance comparison of different modular truss deployable antenna mechanisms.A prototype model of the modular unit mechanism is also developed,with deployment experiments demonstrating the mechanism's simplicity,low DOF,and large deployment ratio.The findings of this study provide a theoretical and technical basis for the future design and development of truss deployable antenna mechanisms.展开更多
The rapid expansion of the low-altitude economy is driving strong demand for highly accurate and reliable positioning technologies to support diverse aerial operations.This review examines core positioning methodologi...The rapid expansion of the low-altitude economy is driving strong demand for highly accurate and reliable positioning technologies to support diverse aerial operations.This review examines core positioning methodologies within the low-altitude intelligent network(LAIN)framework,beginning with an analysis of positioning requirements and performance metrics for low-altitude flight scenarios.It systematically assesses the principles,strengths,and limitations of mainstream positioning systems,including Global Navigation Satellite Systems(GNSS),terrestrial wireless positioning,and autonomous navigation,and it surveys prevalent integrated and cooperative positioning schemes.Our analysis demonstrates that standalone positioning technologies are inadequate in complex low-altitude settings,underscoring the pivotal role of multi-source fusion and unmanned aerial vehicle(UAV)swarm cooperative positioning as future trends.To address infrastructure gaps and high deployment costs in current LAIN systems,we propose a“space−air−ground”integrated and cooperative positioning architecture centered on GNSS and the 5th generation mobile communication technology(5G).The ground layer integrates 5G and GNSS for wide-area enhanced positioning.The aerial layer uses 5G aircraft-to-everything(A2X)and sidelink(SL)communications to build self-organizing networks for cooperative UAV localization.The space layer leverages low Earth orbit(LEO)satellites to overcome coverage limitations in communication and positioning.This hierarchical architecture reduces deployment costs through infrastructure reuse and enables deep integration of communication and navigation capabilities.By supporting collaborative enhancement across all three domains,the framework improves positioning robustness and delivers cost-effective,ubiquitous,and highly reliable positioning services.Finally,we outline promising research directions.This review aims to provide a systematic reference and a novel architectural perspective for the ongoing development of LAIN.展开更多
Dear Editor,As the Internet of things(IoT)and autonomous driving continue to evolve,positioning technology faces increasing demands for higher accuracy and reliability.Traditional positioning methods often struggle in...Dear Editor,As the Internet of things(IoT)and autonomous driving continue to evolve,positioning technology faces increasing demands for higher accuracy and reliability.Traditional positioning methods often struggle in complex signal environments with multipath interference and non-line-of-sight(NLOS)conditions.Reconfigurable intelligent surfaces(RIS),an innovative technology that can flexibly control signal propagation,offer new possibilities for positioning systems.展开更多
In this paper,a novel train positioning method considering satellite raw observation data was proposed,which aims to promote train positioning performance from an innovative perspective of the train satellite-based po...In this paper,a novel train positioning method considering satellite raw observation data was proposed,which aims to promote train positioning performance from an innovative perspective of the train satellite-based positioning error sources.The method focused on overcoming the abnormal observations in satellite observation data caused by railway environment rather than the positioning results.Specifically,the relative positioning experimental platform was built and the zero-baseline method was firstly employed to evaluate the carrier phase data quality,and then,GNSS combined observation models were adopted to construct the detection values,which were applied to judge abnormal-data through the dual-frequency observations.Further,ambiguity fixing optimization was investigated based on observation data selection in partly-blocked environments.The results show that the proposed method can effectively detect and address abnormal observations and improve positioning stability.Cycle slips and gross errors can be detected and identified based on dual-frequency global navigation satellite system data.After adopting the data selection strategy,the ambiguity fixing percentage was improved by 29.2%,and the standard deviation in the East,North,and Up components was enhanced by 12.7%,7.4%,and 12.5%,respectively.The proposed method can provide references for train positioning performance optimization in railway environments from the perspective of positioning error sources.展开更多
The existing Low-Earth-Orbit(LEO)positioning performance cannot meet the requirements of Unmanned Aerial Vehicle(UAV)clusters for high-precision real-time positioning in the Global Navigation Satellite System(GNSS)den...The existing Low-Earth-Orbit(LEO)positioning performance cannot meet the requirements of Unmanned Aerial Vehicle(UAV)clusters for high-precision real-time positioning in the Global Navigation Satellite System(GNSS)denial conditions.Therefore,this paper proposes a UAV Clusters Information Geometry Fusion Positioning(UC-IGFP)method using pseudoranges from the LEO satellites.A novel graph model for linking and computing between the UAV clusters and LEO satellites was established.By utilizing probability to describe the positional states of UAVs and sensor errors,the distributed multivariate Probability Fusion Cooperative Positioning(PF-CP)algorithm is proposed to achieve high-precision cooperative positioning and integration of the cluster.Criteria to select the centroid of the cluster were set.A new Kalman filter algorithm that is suitable for UAV clusters was designed based on the global benchmark and Riemann information geometry theory,which overcomes the discontinuity problem caused by the change of cluster centroids.Finally,the UC-IGFP method achieves the LEO continuous highprecision positioning of UAV clusters.The proposed method effectively addresses the positioning challenges caused by the strong direction of signal beams from LEO satellites and the insufficient constraint quantity of information sources at the edge nodes of the cluster.It significantly improves the accuracy and reliability of LEO-UAV cluster positioning.The results of comprehensive simulation experiments show that the proposed method has a 30.5%improvement in performance over the mainstream positioning methods,with a positioning error of 14.267 m.展开更多
Position sensors are indispensable in robotic joint servo systems for acquiring mechanical positions, yet their installation inevitably occupies an axial space and increases system complexity, limiting their applicabi...Position sensors are indispensable in robotic joint servo systems for acquiring mechanical positions, yet their installation inevitably occupies an axial space and increases system complexity, limiting their applicability in compact robot design where spatial constraints and integration efficiency are critical. Sensorless control reduces mechanical and circuit complexity through hardware simplification, but inherently estimates only the electrical instead of mechanical rotor position information, thus remaining constrained in robot joint control applications. Based on the previously proposed dual-gap dualpole composite machine(DDCM), this paper systematically analyzes the causes of mechanical position estimation errors and proposes a correction method that utilizes a correction coefficient to reduce these errors and enhance estimation accuracy. Furthermore, this paper derives the applicability constraints of the proposed scheme, demonstrating that its requirements for electrical angle position errors are not stringent, thus enabling wide applicability in conventional sensorless control scenarios. The effectiveness of the proposed method is verified by conducting experiments on a 0.75 kW prototype.展开更多
Global Navigation Satellite System(GNSS)-based continuous and accurate train positioning is one of the key technologies for advanced train operations such as train virtual coupling.However,GNSS-based train positioning...Global Navigation Satellite System(GNSS)-based continuous and accurate train positioning is one of the key technologies for advanced train operations such as train virtual coupling.However,GNSS-based train positioning faces significant challenges in real-world scenarios due to environmental complexities and signal interferences.Considering this issue,this paper presents an approach for modeling and performance analysis of GNSS-based train positioning systems using Colored Petri Nets(CPNs).By systematically modeling the GNSS signal reception and processing process,the performance of the positioning system under various environment scenarios is evaluated.The system model integrates three types of interference signals(i.e.,Amplitude Modulation(AM)signals,Frequency Modulation(FM)signals,and pulse signals)while incorporating environmental factors such as terrain obstructions and tunnel shielding.Additionally,the Extended Kalman Filter(EKF)algorithm is employed to process GNSS observation data,providing accurate train position estimations.The simulation results demonstrate that signal interferences and complex environmental conditions significantly affect the GNSS-based positioning accuracy.This study offers a comprehensive framework for evaluating the performance of GNSS-based train positioning systems in different scenarios,highlighting critical factors that influence positioning accuracy and stability.展开更多
In the context of security systems,adequate signal coverage is paramount for the communication between security personnel and the accurate positioning of personnel.Most studies focus on optimizing base station deploym...In the context of security systems,adequate signal coverage is paramount for the communication between security personnel and the accurate positioning of personnel.Most studies focus on optimizing base station deployment under the assumption of static obstacles,aiming to maximize the perception coverage of wireless RF(Radio Frequency)signals and reduce positioning blind spots.However,in practical security systems,obstacles are subject to change,necessitating the consideration of base station deployment in dynamic environments.Nevertheless,research in this area still needs to be conducted.This paper proposes a Dynamic Indoor Environment Beacon Deployment Algorithm(DIE-BDA)to address this problem.This algorithm considers the dynamic alterations in obstacle locations within the designated area.It determines the requisite number of base stations,the requisite time,and the area’s practical and overall signal coverage rates.The experimental results demonstrate that the algorithm can calculate the deployment strategy in 0.12 s following a change in obstacle positions.Experimental results show that the algorithm in this paper requires 0.12 s to compute the deployment strategy after the positions of obstacles change.With 13 base stations,it achieves an effective coverage rate of 93.5%and an overall coverage rate of 97.75%.The algorithm can rapidly compute a revised deployment strategy in response to changes in obstacle positions within security systems,thereby ensuring the efficacy of signal coverage.展开更多
Reliable and accurate cooperative positioning is vital to intelligent connected vehicles(ICVs),in which vehicle-vehicle relative measurements are integrated to provide stable locationaware services.However,in zero-tru...Reliable and accurate cooperative positioning is vital to intelligent connected vehicles(ICVs),in which vehicle-vehicle relative measurements are integrated to provide stable locationaware services.However,in zero-trust autonomous driving environments,the possibility of measurement failures and malicious communication attacks tends to reduce positioning performance.With this in mind,this paper presents an ultra-wide bandwidth(UWB)based cooperative positioning system with the specific objective of ICV localization in zero-trust driving environments.Firstly,to overcome measurement degradation under non-line-ofsight(NLOS)propagation conditions,this study proposes a decentralized 3D cooperative positioning method based on a distributed Kalman filter(DKF)by integrating relative rangeazimuth-elevation measurements,unlike the state-of-the-art methods that rely on only one single relative range information to update motion states.More specifically,in contrast to pioneering studies that mainly focus on the positioning problem arising from only one single type of communication attack(either false data injection(FDI)or denial of service(DoS)),we consider a more challenging case of secure cooperative state estimation under mixed FDI and DoS attacks.To this end,a singular-value decomposition(SVD)-assisted decoupled DKF algorithm is proposed in this work,in which a novel update-triggered inter-vehicular communication mechanism is introduced to ensure robust positioning performance against communication attacks while maintaining low transmission load between individuals.To verify the effectiveness in practical 3D NLOS scenarios,we design an intelligent connected multi-robot platform based on a robot operating system(ROS)and UWB technology.Consequently,extensive experimental results demonstrate its superiority and feasibility by achieving a high positioning accuracy of 0.68 m under adverse attacks,especially in the case of hybrid FDI and DoS attacks.In addition,several critical discussions,including the impact of attack parameters,resilience assessment,and a comparison with event-triggered methods,are provided in this work.Moreover,a demo video has been uploaded in the supplementary materials for a detailed presentation.展开更多
Numerous arthropods evolve and optimize sensory systems, enabling them to effectively adapt complex and competitive habitats. Typically, scorpions can precisely perceive the prey location with the lowest metabolic rat...Numerous arthropods evolve and optimize sensory systems, enabling them to effectively adapt complex and competitive habitats. Typically, scorpions can precisely perceive the prey location with the lowest metabolic rate among invertebrates. This biological phenomenon contrasts sharply with engineered systems, which generally associates high accuracy with substantial energy consumption. Inspired by the Scorpion Compound Slit Sensilla (SCSS) with a stress field modulation strategy, a bionic positioning sensor with superior precision and minimal power consumption is developed for the first time, which utilizes the particular Minimum Positioning Units (MPUs) to efficiently locate vibration signals. The single MPU of the SCSS can recognize the direction of collinear loads by regulating the stress field distribution and further, the coupling action of three MPUs can realize all-angle vibration monitoring in plane. Experiments demonstrate that the bionic positioning sensor achieves 1.43 degrees of angle-error-free accuracy without additional energy supply. As a proof of concept, two bionic positioning sensors and machine learning algorithm are integrated to provide centimeter (cm)-accuracy target localization, ideally suited for the man-machine interaction. The novel design offers a new mechanism for the design of traditional positioning devices, improving precision and efficiency in both the meta-universe and real-world Internet-connected systems.展开更多
Position-sensitive detector(PSD)is widely used in precision measurement fields such as flatness detection,auto-collimator systems,and degrees of freedom testing.However,due to factors such as uneven surface resistance...Position-sensitive detector(PSD)is widely used in precision measurement fields such as flatness detection,auto-collimator systems,and degrees of freedom testing.However,due to factors such as uneven surface resistance and differences in electrode structures,the nonlinearity of PSD becomes increasingly severe as the photosensitive surface moves from the center toward the edges of the four electrodes.To address this issue,a PSD nonlinearity correction algorithm is proposed.The algorithm utilizes the particle swarm optimization(PSO)algorithm to determine the optimal weights and thresholds,providing better initial parameters for the back propagation(BP)neural network.The BP neural network then iterates continuously until the error conditions are met,completing the correction process.Furthermore,a PSD nonlinearity correction system was developed,and the influence of different spot sizes on PSD positioning accuracy was simulated based on the current equation under the Gaussian spot model.This validated the robustness of the correction algorithm under varying spot sizes.The results demonstrate that the overall optimized error is reduced by 84.51%,and for spot sizes smaller than 1 mm,the error reduction exceeds 93.89%.This method not only meets the measurement accuracy requirements but also extends the measurement range of PSD.展开更多
This study explores the use of the Global Navigation Satellite System(GNSS)precise point positioning(PPP)technology to determine the natural vibration periods of towering structures through simulations and field testi...This study explores the use of the Global Navigation Satellite System(GNSS)precise point positioning(PPP)technology to determine the natural vibration periods of towering structures through simulations and field testing.During the simulation phase,a GNSS receiver captured vi-bration waveforms generated by a single-axis motion simulator based on preset signal parameters,analyzing how different satellite system configurations affect the efficiency of extracting vibration parameters.Subsequently,field tests were conducted on a high-rise steel singletube tower.The results indicate that in the simulation environment,no matter the PPP positioning data under single GPS or multisystem combination,the vibration frequency of singleaxis motion simulator can be accurately extracted after frequency do-main analysis,with multisystem setups providing more precise amplitude parameters.In the field test,the natural vibration periods of the main vibration modes of high-rise steel single-tube tower measured by PPP technology closely match the results of the first two modes derived from finite element analysis.The first mode period calculated by the em-pirical formula is approximately 6%higher than those determined through finite element analysis and PPP.This study demonstrates the potential of PPP for structural vibration analysis,offering significant benefits for assessing dynamic responses and monitoring the health of towering structures.展开更多
文摘Severe acute pancreatitis(SAP)can induce acute respiratory distress syndrome(ARDS)and abdominal compartment syndrome(ACS).Although prone position ventilation(PPV)can improve outcomes in patients with ARDS,there is significant controversy regarding its concurrent use with ACS owing to concerns of increased risk of intra-abdominal pressure(IAP).[1]We present a case of successful PPV application without adverse eff ects.
文摘Background:Pressure injury(PI)is a prevalent complication in pediatric cardiac surgery,with higher incidence than in general pediatric populations due to children’s thin skin,underdeveloped subcutaneous tissue,and prolonged intraoperative pressure.Objective:To evaluate the effectiveness of the curvilinear supine position(CSP)in preventing PI among children undergoing congenital heart disease(CHD)surgery.Methods:Between October 2024 and February 2025,a single-center randomized controlled trial was conducted.Of the 80 children initially enrolled for congenital heart disease(CHD)surgery,77(aged 1 month to 14 years)completed the study and were included in the final analysis after 3 were excluded due to protocol violations.Participants were randomly assigned to the CSP group(n=38)or the conventional supine position group(n=39).Results:The incidence of PI was significantly lower in the CSP group(2.6%)compared to the control group(20.5%)(p=0.029).Postoperative LDH levels were also significantly reduced in the CSP group(422.67±86.52 U/L vs.592.92±215.71 U/L;p=0.031),while preoperative LDH and surgical variables(e.g.,cardiopulmonary bypass time)were comparable between groups.Although the CSP group had a shorter hospital stay(17.24 vs.22.51 days),the difference was not statistically significant(p=0.085).Caregiver satisfaction was significantly higher in the CSP group(100.0%vs.84.6%;p=0.025).Conclusion:CSP effectively reduces PI incidence,mitigates tissue injury,and enhances caregiver satisfaction in pediatric cardiac surgery,offering a safe and feasible strategy for perioperative PI prevention.
基金co-supported by the National Natural Science Foundation of China(No.52125504)the Liaoning Revitalization Talents Program(No.XLYC2202017)Dalian Support Policy Project for Innovation of Technological Talents(No.2023RG001)。
文摘The high-quality assembly of Large Aircraft Components(LACs)is essential in modern aviation manufacturing.Numerical control locators are employed for the posture adjustment of LAC,yet the system's multi-input multi-output,nonlinearity,and strong coupling presents significant challenges.The substantial internal force generated during the adjustment process can potentially damage the LAC and degrade the assembly quality.Hence,a workspace-based hybrid force position control scheme was developed to achieve high quality assembly with high-precision and lower internal force.Firstly,an offline workspace analysis with inherent geometric characteristics to form time-varying posture error constraint.Then,the posture error is integrated into the online position axis control to ensure tracking the ideal posture,while the force control axis compensates for posture deviation by minimizing internal force,thereby achieving high precision and low internal force.Finally,the effectiveness was demonstrated through experiments.The root mean square errors of orientation and position are 104 rad and 0.1 mm,respectively.A reduction in internal force can range from 10.96%to 57.4%compared to the traditional method.Key points'max position error is decreased from 0.32 mm to 0.18 mm,satisfying the 0.5 mm tolerance.Therefore,the proposed method will help promote the development of high-performance manufacturing.
基金financially supported by the National Natural Science Foundation of China (Nos.22375024,21975031,51933001,and 21734009)。
文摘The fluorination strategy has been proven effective in significantly enhancing the photovoltaic performance of organic solar cells(OSCs) based on non-fused ring electron acceptors(NFREAs).However,research on the impact of fluorination positions at side chains on NFREAs device performance remains scant.In this study,we introduce two isomeric NFREAs,designated as GA-2F-E and GA-2F,distinguished by their fluorination positions at the side chains.Both NFREAs share a thiophene[3,2-b]thiophene core,but their side chains differ:GA-2F-E features two(4-butylphenyl)-N-(4-fluorophenyl) amino groups,whereas GA-2F's side chains consist of bis(4-fluorophenyl)amino and bis(4-butylphenyl)amino groups attached to opposite sides of the core.To delve into the influence of fluorination positions on the optoelectronic properties,aggregation behavior,and overall efficiency of the acceptor molecules,a comprehensive investigation was conducted.The findings reveal that,despite similar photophysical properties and comparable absorption bandwidths,GA-2F-E,with fluorine atoms positioned on both sides of the molecular framework,demonstrates more compact π-π stacking,reduced bimolecular recombination,superior exciton transport,and a more balanced,higher mobility.As a result of these advantages,OSCs optimized with D18:GA-2F-E achieve a remarkable power conversion efficiency(PCE) of 16.45 %,surpassing the 15.83 %PCE of devices utilizing D18:GA-2F.This research underscores the potential of NFREAs in future applications and highlights the significance of fluorination positions in enhancing OSC performance,paving the way for the development of more efficient NFREAs.
基金Supported by the Zhejiang Medical Health Science and Technology Project(No.2021KY217)the Basic Public Welfare Research Project of Wenzhou Municipal Science and Technology Bureau(No.2024Y1221).
文摘AIM:To evaluate and compare alterations in the effective lens position(ELP)and refractive outcomes among three distinct intraocular lens(IOL)types.METHODS:Patients with cataracts were enrolled and allocated to 3 groups:Group A(implanted with the SN6CWS),Group B(implanted with the MI60),and Group C(implanted with the Aspira-aA).ELP measurements were obtained with swept-source optical coherence tomography(SS-OCT)at 1d,1wk,1mo,and 3mo postoperatively.Subjective refraction assessments were conducted at 1wk,1mo,and 3mo following surgery.RESULTS:The study included 189 eyes of 150 cataract patients(66 males).There were 77 eyes in Group A,55 eyes in Group B,and 57 eyes in Group C.The root mean square of the ELP(ELPRMS)within the initial 3mo was significantly lower for Group A than for Groups B and C.Refractive changes within Group A were not significant across the time points of 1wk,1mo,and 3mo.Conversely,both Group B and Group C demonstrated statistically significant shifts toward hyperopia from 1wk to 3mo postsurgery.CONCLUSION:Among the three IOLs examined,the SN6CWS IOL showes the greatest stability during the first 3mo postoperatively.Between 1wk and 3mo after surgery,notable hyperopic shifts are evident in eyes implanted with the MI60 and Aspira-aA IOLs,whereas refractive outcomes remain relatively constant in eyes implanted with SN6CWS IOLs.
基金partially supported by the National Natural Science Foundation of China(Nos.61901494,62101563)。
文摘Rotating Single-Baseline Interferometer(RSBI)systems have attracted considerable attention for Direct Position Determination(DPD)due to their simplicity and high localization accuracy.Nevertheless,the growing complexity of electromagnetic environments has led to scenarios with multiple time-frequency aliased sources,rendering conventional DPD methods for RSBI systems ineffective.Previous studies have predominantly concentrated on deploying antenna arrays and applying related signal-processing techniques for localization.Typically,these approaches necessitate that the number of physical antennas exceeds the number of sources.For RSBI systems already in practical operation,this would entail the installation of additional physical antennas,which implies equipment recycling and hardware upgrades.In numerous cases,such modifications are unfeasible.This paper proposes a novel Relative Offset-based Direct Position Determination(RO-DPD)method for RSBI systems that can handle multiple time-frequency aliased sources.The proposed method overcomes the challenge of simultaneous positioning without requiring hardware modifications by leveraging time accumulation and algorithmic enhancements.The implementation of the method involves three key steps.Firstly,the rotation of the interferometer is synthesized into a virtual Uniform Circular Array(UCA).Secondly,a novel estimation variable,termed relative offset,is introduced.The variable serves as an intermediate parameter to establish correlation equations between the positions of multiple time-frequency aliased sources and the intercepted signals.Thirdly,the relative offset model in the UCA is transformed into a virtual Uniform Linear Array(ULA)model,from which the cost function can be derived via the Spatial Smoothing(SS)MUSIC algorithm.Theoretical analysis and simulation results verify the effectiveness of the proposed method.Compared with traditional approaches,the RO-DPD method maintains the low complexity of RSBI systems while demonstrating robust performance in complex electromagnetic environments.
基金supported in part by the National Natural Science Foundation of China under Grant 52477060in part by the Tianjin Natural Science Foundation Project under Grant 24JCZDJC00250in part by the Zhejiang Leading Innovation and Entrepreneurship Team Project under Grant 2024R01012.
文摘In position-sensorless brushless direct current(DC)motors(BLDCMs)fed by a four-switch three-phase(FSTP)inverter,only two phases are fully controlled,while the remaining phase is tied to the midpoint of the split DC-link capacitors.The voltage pulses required by inductance-based initial position detection can cause unequal discharge of the series capacitors,shifting the neutral-point voltage away from half of DC-link voltage(U_(dc)/2).This neutral-point drift breaks the spatial symmetry of the inverter voltage vectors,so the 360°electrical period can no longer be evenly partitioned into six sectors during initial rotor position detection.To address this issue,this paper proposes a detection-pulse injection sequence that explicitly accounts for the asymmetric voltage vectors of the FSTP inverter.With the proposed sequence,the initial rotor position can be identified within a 30°electrical sector.The method requires no additional voltage or current sensors,and experimental results confirm its feasibility.
文摘Deep learning has been recognized as an effective method for indoor positioning.However,most existing real-valued neural networks(RVNNs)treat the two constituent components of complex-valued channel state information(CSI)as real-valued inputs,potentially discarding useful information embedded in the original CSI.In addition,existing positioning models generally face the contradiction between computational complexity and positioning accuracy.To address these issues,we combine graph neural network(GNN)with complex-valued neural network(CVNN)to construct a lightweight indoor positioning model named CGNet.CGNet employs complexvalued convolution operation to directly process the original CSI data,fully exploiting the correlation between real and imaginary parts of CSI while extracting local features.Subsequently,the feature values are treated as nodes,and conditional position encoding(CPE)module is applied to add positional information.To reduce the number of connections in the graph structure and lower themodel complexity,feature information is mapped to an efficient graph structure through a dynamic axial graph construction(DAGC)method,with global features extracted usingmaximum relative graph convolution(MRConv).Experimental results show that,on the CTW dataset,CGNet achieves a 10%improvement in positioning accuracy compared to existing methods,while the number of model parameters is only 0.8 M.CGNet achieves excellent positioning accuracy with very few parameters.
基金sponsored by the National Natural Science Foundation of China(No.52075467)Hebei Province Fund Outstanding Youth Fund Project,China(No.E2024203107)。
文摘Modular truss space deployable antennas are key for future large aperture,high precision antennas,already proven in various in-orbit applications globally.This paper introduces a design method for a tetrahedral basic unit mechanism with dual height positioning nodes.A parametric model is established,and its DOF are analyzed to confirm the mechanism's validity.The new tetrahedral basic unit mechanism constructed by this method is a single DOF mechanism and can locate different parabolic node heights.In order to further adapt to the parabolic and large aperture requirements of the deployable antenna of the truss,a combination unit and modular unit mechanism are developed based on this tetrahedral unit.The DOF and deployment characteristics of the modular unit mechanism are analyzed and validated through simulations.Various networking methods for the modular units are proposed,followed by a comprehensive performance comparison of different modular truss deployable antenna mechanisms.A prototype model of the modular unit mechanism is also developed,with deployment experiments demonstrating the mechanism's simplicity,low DOF,and large deployment ratio.The findings of this study provide a theoretical and technical basis for the future design and development of truss deployable antenna mechanisms.
基金supported by the National Key Research&Development Program of China(No.2024YFB3910102).
文摘The rapid expansion of the low-altitude economy is driving strong demand for highly accurate and reliable positioning technologies to support diverse aerial operations.This review examines core positioning methodologies within the low-altitude intelligent network(LAIN)framework,beginning with an analysis of positioning requirements and performance metrics for low-altitude flight scenarios.It systematically assesses the principles,strengths,and limitations of mainstream positioning systems,including Global Navigation Satellite Systems(GNSS),terrestrial wireless positioning,and autonomous navigation,and it surveys prevalent integrated and cooperative positioning schemes.Our analysis demonstrates that standalone positioning technologies are inadequate in complex low-altitude settings,underscoring the pivotal role of multi-source fusion and unmanned aerial vehicle(UAV)swarm cooperative positioning as future trends.To address infrastructure gaps and high deployment costs in current LAIN systems,we propose a“space−air−ground”integrated and cooperative positioning architecture centered on GNSS and the 5th generation mobile communication technology(5G).The ground layer integrates 5G and GNSS for wide-area enhanced positioning.The aerial layer uses 5G aircraft-to-everything(A2X)and sidelink(SL)communications to build self-organizing networks for cooperative UAV localization.The space layer leverages low Earth orbit(LEO)satellites to overcome coverage limitations in communication and positioning.This hierarchical architecture reduces deployment costs through infrastructure reuse and enables deep integration of communication and navigation capabilities.By supporting collaborative enhancement across all three domains,the framework improves positioning robustness and delivers cost-effective,ubiquitous,and highly reliable positioning services.Finally,we outline promising research directions.This review aims to provide a systematic reference and a novel architectural perspective for the ongoing development of LAIN.
基金supported by the Open Fund Project of Key Laboratory of Ocean Observation Technology,MNR(2023klootA01).
文摘Dear Editor,As the Internet of things(IoT)and autonomous driving continue to evolve,positioning technology faces increasing demands for higher accuracy and reliability.Traditional positioning methods often struggle in complex signal environments with multipath interference and non-line-of-sight(NLOS)conditions.Reconfigurable intelligent surfaces(RIS),an innovative technology that can flexibly control signal propagation,offer new possibilities for positioning systems.
基金Project(52272339)supported by the National Natural Science Foundation of ChinaProject(2023YFB390730303)supported by the National Key Research and Development Program of China+2 种基金Project(L2023G004)supported by the Science and Technology Research and Development Program of China State Railway Group Co.,Ltd.Project(QZKFKT2023-005)supported by the State Key Laboratory of Heavy-duty and Express High-power Electric Locomotive,ChinaProject(2022JZZ05)supported by the Open Foundation of MOE Key Laboratory of Engineering Structures of Heavy Haul Railway(Central South University),China。
文摘In this paper,a novel train positioning method considering satellite raw observation data was proposed,which aims to promote train positioning performance from an innovative perspective of the train satellite-based positioning error sources.The method focused on overcoming the abnormal observations in satellite observation data caused by railway environment rather than the positioning results.Specifically,the relative positioning experimental platform was built and the zero-baseline method was firstly employed to evaluate the carrier phase data quality,and then,GNSS combined observation models were adopted to construct the detection values,which were applied to judge abnormal-data through the dual-frequency observations.Further,ambiguity fixing optimization was investigated based on observation data selection in partly-blocked environments.The results show that the proposed method can effectively detect and address abnormal observations and improve positioning stability.Cycle slips and gross errors can be detected and identified based on dual-frequency global navigation satellite system data.After adopting the data selection strategy,the ambiguity fixing percentage was improved by 29.2%,and the standard deviation in the East,North,and Up components was enhanced by 12.7%,7.4%,and 12.5%,respectively.The proposed method can provide references for train positioning performance optimization in railway environments from the perspective of positioning error sources.
基金supported in part by the National Natural Science Foundation of China(Nos.62171375,62271397,62001392,62101458,62173276,61803310 and 61801394)the Shenzhen Science and Technology Innovation ProgramChina(No.JCYJ20220530161615033)。
文摘The existing Low-Earth-Orbit(LEO)positioning performance cannot meet the requirements of Unmanned Aerial Vehicle(UAV)clusters for high-precision real-time positioning in the Global Navigation Satellite System(GNSS)denial conditions.Therefore,this paper proposes a UAV Clusters Information Geometry Fusion Positioning(UC-IGFP)method using pseudoranges from the LEO satellites.A novel graph model for linking and computing between the UAV clusters and LEO satellites was established.By utilizing probability to describe the positional states of UAVs and sensor errors,the distributed multivariate Probability Fusion Cooperative Positioning(PF-CP)algorithm is proposed to achieve high-precision cooperative positioning and integration of the cluster.Criteria to select the centroid of the cluster were set.A new Kalman filter algorithm that is suitable for UAV clusters was designed based on the global benchmark and Riemann information geometry theory,which overcomes the discontinuity problem caused by the change of cluster centroids.Finally,the UC-IGFP method achieves the LEO continuous highprecision positioning of UAV clusters.The proposed method effectively addresses the positioning challenges caused by the strong direction of signal beams from LEO satellites and the insufficient constraint quantity of information sources at the edge nodes of the cluster.It significantly improves the accuracy and reliability of LEO-UAV cluster positioning.The results of comprehensive simulation experiments show that the proposed method has a 30.5%improvement in performance over the mainstream positioning methods,with a positioning error of 14.267 m.
基金supported in part by the National Natural Science Foundation of China under Grants 52277057 and U22A20217in part by the Shandong Youth Innovation Team under Grant 2022KJ150。
文摘Position sensors are indispensable in robotic joint servo systems for acquiring mechanical positions, yet their installation inevitably occupies an axial space and increases system complexity, limiting their applicability in compact robot design where spatial constraints and integration efficiency are critical. Sensorless control reduces mechanical and circuit complexity through hardware simplification, but inherently estimates only the electrical instead of mechanical rotor position information, thus remaining constrained in robot joint control applications. Based on the previously proposed dual-gap dualpole composite machine(DDCM), this paper systematically analyzes the causes of mechanical position estimation errors and proposes a correction method that utilizes a correction coefficient to reduce these errors and enhance estimation accuracy. Furthermore, this paper derives the applicability constraints of the proposed scheme, demonstrating that its requirements for electrical angle position errors are not stringent, thus enabling wide applicability in conventional sensorless control scenarios. The effectiveness of the proposed method is verified by conducting experiments on a 0.75 kW prototype.
基金supported by the National Key Research and Development Program of China(2023YFB3907300)the Fundamental Research Funds for the Central Universities(2024JBMC002)the National Natural Science Foundation of China(T2222015,U2268206).
文摘Global Navigation Satellite System(GNSS)-based continuous and accurate train positioning is one of the key technologies for advanced train operations such as train virtual coupling.However,GNSS-based train positioning faces significant challenges in real-world scenarios due to environmental complexities and signal interferences.Considering this issue,this paper presents an approach for modeling and performance analysis of GNSS-based train positioning systems using Colored Petri Nets(CPNs).By systematically modeling the GNSS signal reception and processing process,the performance of the positioning system under various environment scenarios is evaluated.The system model integrates three types of interference signals(i.e.,Amplitude Modulation(AM)signals,Frequency Modulation(FM)signals,and pulse signals)while incorporating environmental factors such as terrain obstructions and tunnel shielding.Additionally,the Extended Kalman Filter(EKF)algorithm is employed to process GNSS observation data,providing accurate train position estimations.The simulation results demonstrate that signal interferences and complex environmental conditions significantly affect the GNSS-based positioning accuracy.This study offers a comprehensive framework for evaluating the performance of GNSS-based train positioning systems in different scenarios,highlighting critical factors that influence positioning accuracy and stability.
文摘In the context of security systems,adequate signal coverage is paramount for the communication between security personnel and the accurate positioning of personnel.Most studies focus on optimizing base station deployment under the assumption of static obstacles,aiming to maximize the perception coverage of wireless RF(Radio Frequency)signals and reduce positioning blind spots.However,in practical security systems,obstacles are subject to change,necessitating the consideration of base station deployment in dynamic environments.Nevertheless,research in this area still needs to be conducted.This paper proposes a Dynamic Indoor Environment Beacon Deployment Algorithm(DIE-BDA)to address this problem.This algorithm considers the dynamic alterations in obstacle locations within the designated area.It determines the requisite number of base stations,the requisite time,and the area’s practical and overall signal coverage rates.The experimental results demonstrate that the algorithm can calculate the deployment strategy in 0.12 s following a change in obstacle positions.Experimental results show that the algorithm in this paper requires 0.12 s to compute the deployment strategy after the positions of obstacles change.With 13 base stations,it achieves an effective coverage rate of 93.5%and an overall coverage rate of 97.75%.The algorithm can rapidly compute a revised deployment strategy in response to changes in obstacle positions within security systems,thereby ensuring the efficacy of signal coverage.
基金supported in part by the National Natural Science Foundation of China(62273065,62003064,62303386)the Natural Science Foundation of Chongqing(CSTB2023NSCQ-LZX0014)+1 种基金the Science and Technology Research Program of Chongqing Municipal Education Commission(KJZDK201800701,KJQN202000717)Sichuan Science and Technology Program(2024NSFSC0525).
文摘Reliable and accurate cooperative positioning is vital to intelligent connected vehicles(ICVs),in which vehicle-vehicle relative measurements are integrated to provide stable locationaware services.However,in zero-trust autonomous driving environments,the possibility of measurement failures and malicious communication attacks tends to reduce positioning performance.With this in mind,this paper presents an ultra-wide bandwidth(UWB)based cooperative positioning system with the specific objective of ICV localization in zero-trust driving environments.Firstly,to overcome measurement degradation under non-line-ofsight(NLOS)propagation conditions,this study proposes a decentralized 3D cooperative positioning method based on a distributed Kalman filter(DKF)by integrating relative rangeazimuth-elevation measurements,unlike the state-of-the-art methods that rely on only one single relative range information to update motion states.More specifically,in contrast to pioneering studies that mainly focus on the positioning problem arising from only one single type of communication attack(either false data injection(FDI)or denial of service(DoS)),we consider a more challenging case of secure cooperative state estimation under mixed FDI and DoS attacks.To this end,a singular-value decomposition(SVD)-assisted decoupled DKF algorithm is proposed in this work,in which a novel update-triggered inter-vehicular communication mechanism is introduced to ensure robust positioning performance against communication attacks while maintaining low transmission load between individuals.To verify the effectiveness in practical 3D NLOS scenarios,we design an intelligent connected multi-robot platform based on a robot operating system(ROS)and UWB technology.Consequently,extensive experimental results demonstrate its superiority and feasibility by achieving a high positioning accuracy of 0.68 m under adverse attacks,especially in the case of hybrid FDI and DoS attacks.In addition,several critical discussions,including the impact of attack parameters,resilience assessment,and a comparison with event-triggered methods,are provided in this work.Moreover,a demo video has been uploaded in the supplementary materials for a detailed presentation.
基金supported by the National Natural Science Foundation of China(No.52175269)the Foundation for Innovative Research Groups of the National Natural Science Foundation of China(No.52021003)+2 种基金Science and Technology Research Project of Education Department of Jilin Province(JJKH20231146KJ,JJKH20241262KJ)Project ZR2024ME104 supported by Shandong Provincial Natural Science FoundationChina Postdoctoral Science Foundation(No.2024M751086).
文摘Numerous arthropods evolve and optimize sensory systems, enabling them to effectively adapt complex and competitive habitats. Typically, scorpions can precisely perceive the prey location with the lowest metabolic rate among invertebrates. This biological phenomenon contrasts sharply with engineered systems, which generally associates high accuracy with substantial energy consumption. Inspired by the Scorpion Compound Slit Sensilla (SCSS) with a stress field modulation strategy, a bionic positioning sensor with superior precision and minimal power consumption is developed for the first time, which utilizes the particular Minimum Positioning Units (MPUs) to efficiently locate vibration signals. The single MPU of the SCSS can recognize the direction of collinear loads by regulating the stress field distribution and further, the coupling action of three MPUs can realize all-angle vibration monitoring in plane. Experiments demonstrate that the bionic positioning sensor achieves 1.43 degrees of angle-error-free accuracy without additional energy supply. As a proof of concept, two bionic positioning sensors and machine learning algorithm are integrated to provide centimeter (cm)-accuracy target localization, ideally suited for the man-machine interaction. The novel design offers a new mechanism for the design of traditional positioning devices, improving precision and efficiency in both the meta-universe and real-world Internet-connected systems.
基金Supported by the National Natural Science Foundation of China(U1831133)Open Fund of Key Laboratory of Space Active Optoelectronics Technology,Chinese Academy of Sciences(2021ZDKF4)。
文摘Position-sensitive detector(PSD)is widely used in precision measurement fields such as flatness detection,auto-collimator systems,and degrees of freedom testing.However,due to factors such as uneven surface resistance and differences in electrode structures,the nonlinearity of PSD becomes increasingly severe as the photosensitive surface moves from the center toward the edges of the four electrodes.To address this issue,a PSD nonlinearity correction algorithm is proposed.The algorithm utilizes the particle swarm optimization(PSO)algorithm to determine the optimal weights and thresholds,providing better initial parameters for the back propagation(BP)neural network.The BP neural network then iterates continuously until the error conditions are met,completing the correction process.Furthermore,a PSD nonlinearity correction system was developed,and the influence of different spot sizes on PSD positioning accuracy was simulated based on the current equation under the Gaussian spot model.This validated the robustness of the correction algorithm under varying spot sizes.The results demonstrate that the overall optimized error is reduced by 84.51%,and for spot sizes smaller than 1 mm,the error reduction exceeds 93.89%.This method not only meets the measurement accuracy requirements but also extends the measurement range of PSD.
基金The National Natural Science Foundation of China(No.41974214).
文摘This study explores the use of the Global Navigation Satellite System(GNSS)precise point positioning(PPP)technology to determine the natural vibration periods of towering structures through simulations and field testing.During the simulation phase,a GNSS receiver captured vi-bration waveforms generated by a single-axis motion simulator based on preset signal parameters,analyzing how different satellite system configurations affect the efficiency of extracting vibration parameters.Subsequently,field tests were conducted on a high-rise steel singletube tower.The results indicate that in the simulation environment,no matter the PPP positioning data under single GPS or multisystem combination,the vibration frequency of singleaxis motion simulator can be accurately extracted after frequency do-main analysis,with multisystem setups providing more precise amplitude parameters.In the field test,the natural vibration periods of the main vibration modes of high-rise steel single-tube tower measured by PPP technology closely match the results of the first two modes derived from finite element analysis.The first mode period calculated by the em-pirical formula is approximately 6%higher than those determined through finite element analysis and PPP.This study demonstrates the potential of PPP for structural vibration analysis,offering significant benefits for assessing dynamic responses and monitoring the health of towering structures.
