60 GHz millimeter wave(mmWave)system provides extremely high time resolution and multipath components(MPC)separation and has great potential to achieve high precision in the indoor positioning.However,the ranging data...60 GHz millimeter wave(mmWave)system provides extremely high time resolution and multipath components(MPC)separation and has great potential to achieve high precision in the indoor positioning.However,the ranging data is often contaminated by non-line-of-sight(NLOS)transmission.First,six features of 60GHz mm Wave signal under LOS and NLOS conditions are evaluated.Next,a classifier constructed by random forest(RF)algorithm is used to identify line-of-sight(LOS)or NLOS channel.The identification mechanism has excellent generalization performance and the classification accuracy is over 97%.Finally,based on the identification results,a residual weighted least squares positioning method is proposed.All ranging information including that under NLOS channels is fully utilized,positioning failure caused by insufficient LOS links can be avoided.Compared with the conventional least squares approach,the positioning error of the proposed algorithm is reduced by 49%.展开更多
The accuracy of spot centroid positioning has a significant impact on the tracking accuracy of the system and the stability of the laser link construction.In satellite laser communication systems,the use of short-wave...The accuracy of spot centroid positioning has a significant impact on the tracking accuracy of the system and the stability of the laser link construction.In satellite laser communication systems,the use of short-wave infrared wavelengths as beacon light can reduce atmospheric absorption and signal attenuation.However,there are strong non-uniformity and blind pixels in the short-wave infrared image,which makes the image distorted and leads to the decrease of spot centroid positioning accuracy.Therefore,the high-precision localization of the spot centroid of the short-wave infrared images is of great research significance.A high-precision spot centroid positioning model for short-wave infrared is proposed to correct for non-uniformity and blind pixels in short-wave infrared images and quantify the localization errors caused by the two,further model-based localization error simulations are performed,and a novel spot centroid positioning payload for satellite laser communications has been designed using the latest 640×512 planar array InGaAs shortwave infrared detector.The experimental results show that the non-uniformity of the corrected image is reduced from 7%to 0.6%,the blind pixels rejection rate reaches 100%,the frame rate can be up to 2000 Hz,and the spot centroid localization accuracy is as high as 0.1 pixel point,which realizes high-precision spot centroid localization of high-frame-frequency short-wave infrared images.展开更多
Traditionally, basis weight control valve is driven by a constant frequency pulse signal. Therefore, it is difficult for the valve to match the control precision of basis weight. Dynamic simulation research using Matl...Traditionally, basis weight control valve is driven by a constant frequency pulse signal. Therefore, it is difficult for the valve to match the control precision of basis weight. Dynamic simulation research using Matlab/Simulink indicates that there is much more overshoot and fluctuating during the valve-positioning process. In order to improve the valve-positioning precision, the control method of trapezoidal velocity curve was studied. The simulation result showed that the positioning steady-state error was less than 0.0056%, whereas the peak error was less than 0.016% by using trapezoidal velocity curve at 10 positioning steps. A valve-positioning precision experimental device for the stepper motor of basis weight control valve was developed. The experiment results showed that the error ratio of 1/10000 positioning steps was 4% by using trapezoidal velocity curve. Furthermore, the error ratio of 10/10000 positioning steps was 0.5%. It proved that the valve-positioning precision of trapezoidal velocity curve was much higher than that of the constant frequency pulse signal control strategy. The new control method of trapezoidal velocity curve can satisfy the precision requirement of 10000 steps.展开更多
Selecting the optimal reference satellite is an important component of high-precision relat/ve positioning because the reference satellite directly influences the strength of the normal equation. The reference satelli...Selecting the optimal reference satellite is an important component of high-precision relat/ve positioning because the reference satellite directly influences the strength of the normal equation. The reference satellite selection methods based on elevation and positional dilution of precision （PDOP） value were compared. Results show that all the above methods cannot select the optimal reference satellite. We introduce condition number of the design matrix in the reference satellite selection method to improve structure of the normal equation, because condition number can indicate the ill condition of the normal equation. The experimental results show that the new method can improve positioning accuracy and reliability in precise relative positioning.展开更多
Multi-sensor coordinate unification in dimensional metrology is used in order to get holistic, more accurate and reliable information about a workpiece based on several or multiple measurement values from ...Multi-sensor coordinate unification in dimensional metrology is used in order to get holistic, more accurate and reliable information about a workpiece based on several or multiple measurement values from one or more sensors. Because of the problem that standard ball is deficient as a standard artifact in the coordinate unification of high-precision composite measurement in two dimensions （2D） , a new method is proposed in this paper which uses angle gauge blocks as standard artifacts to achieve coordinate unification between the image sensor and the tactile probe. By comparing the standard ball with the angle gauge block as a standard artifact, theoretical analysis and experimental results are given to prove that it is more precise and more convenient to use angle gauge blocks as standard artifacts to achieve coordinate unification of high-precision composite measurement in two dimensions.展开更多
A rock-drilling jumbo is the main piece of tunneling equipment used in the energy and infrastructure industries in various countries.The positioning accuracy of its drilling boom greatly affects tunneling efficiency a...A rock-drilling jumbo is the main piece of tunneling equipment used in the energy and infrastructure industries in various countries.The positioning accuracy of its drilling boom greatly affects tunneling efficiency and section-forming quality of mine roadways and engineering tunnels.In order to improve the drilling-positioning accuracy of a three-boom drilling jumbo,we established a kinematics model of the multi-degree-of-freedom(multi-DOF)multi-boom system,using the improved Denavit-Hartenberg(D-H)method,and obtained the mapping relationship between the end position and the amount of motion of each joint.The error of the inverse kinematics calculation for the drilling boom is estimated by an analytical method and a global search algorithm based on particle swarm optimization(PSO)for a straight blasting hole and an inclined blasting hole.On this basis,we propose a back-propagation(BP)neural network optimized by an improved sparrow search algorithm(ISSA)to predict the positioning error of the drilling booms of a three-boom drilling jumbo.In order to verify the accuracy of the proposed error compensation model,we built an automatic-control test platform for the boom,and carried out a positioning error compensation test on the boom.The results show that the average drilling-positioning error was reduced from 9.79 to 5.92 cm,and the error was reduced by 39.5%.Therefore,the proposed method effectively reduces the positioning error of the drilling boom,and improves the accuracy and efficiency of rock drilling.展开更多
Zenith Tropospheric Delay(ZTD)is an important factor that restricts the high-precision positioning of global navigation satellite system(GNSS),and it is of great significance in establishing a real-time and highprecis...Zenith Tropospheric Delay(ZTD)is an important factor that restricts the high-precision positioning of global navigation satellite system(GNSS),and it is of great significance in establishing a real-time and highprecision ZTD model.However,existing ZTD models only consider the impact of linear terms on ZTD estimation,whereas the nonlinear factors have rarely been investigated before and thus become the focus of this study.A real-time and high-precision ZTD model for large height difference area is proposed by considering the linear and nonlinear characteristics of ZTD spatiotemporal variations and is called the realtime linear and nonlinearity ZTD(RLNZ)model.This model uses the ZTD estimated from the Global Pressure and Temperature 3(GPT3)model as the initial value.The linear impacts of periodic term and height on the estimation of ZTD difference between GNSS and GPT3 model are first considered.In addition,nonlinear factors such as geographical location and time are further used to fit the remaining nonlinear ZTD residuals using the general regression neural network method.Finally,the RLNZ-derived ZTD is obtained at an arbitrary location.The western United States,with height difference ranging from-500 to 4000 m,is selected,and the hourly ZTD of 484 GNSS stations provided by the Nevada Geodetic Laboratory(NGL)and the data of 9 radiosonde(RS)stations in the year 2021 are used.Experiment results show that a better performance of ZTD estimation can be retrieved from the proposed RLNZ model when compared with the GPT3 model.Statistical results show the averaged root mean square(RMS),Bias,and mean absolute error(MAE)of ZTD from GPT3 and RLNZ models are 33.7/0.8/25.7 mm and 22.6/0.1/17.4 mm,respectively.The average improvement rate of the RLNZ model is 33% when compared to the GPT3 model.Finally,the application of the proposed RLNZ model in simulated real-time Precise Point Positioning(PPP)indicates that the accuracy of PPP in N,E and U components is improved by 8%,2%,and 6% when compared with that from the GPT3-based PPP.Meanwhile,the convergence time in N and U components is improved by 23% and 7%,respectively.Such results verify the superiority of the proposed RLNZ model in retrieving realtime ZTD maps for GNSS positioning and navigation applications.展开更多
Precise coseismic displacements in earthquake/tsunamic early warning are necessary to characterize earthquakes in real time in order to enable decision-makers to issue alerts for public safety.Real-time global navigat...Precise coseismic displacements in earthquake/tsunamic early warning are necessary to characterize earthquakes in real time in order to enable decision-makers to issue alerts for public safety.Real-time global navigation satellite systems(GNSSs)have been a valuable tool in monitoring seismic motions,allowing permanent displacement computation to be unambiguously achieved.As a valuable tool presented to the seismic commu nity,the GSeisRT software developed by Wuhan University(China)can realize multi-GNSS precise point positioning with ambiguity resolution(PPP-AR)and achieve centimeterlevel to sub-centimeter-level precision in real time.While the stable maintenance of a global precise point positioning(PPP)service is challenging,this software is capable of estimating satellite clocks and phase biases in real time using a regional GNSS network.This capability makes GSeisRT especially suitable for proprietary GNSS networks and,more importantly,the highest possible positio ning precision and reliability can be obtained.According to real-time results from the Network of the Americas,the mean root mean square(RMS)errors of kinematic PPP-AR over a 24 h span are as low as 1.2,1.3,and 3.0 cm in the east,north,and up components,respectively.Within the few minutes that span a typical seismic event,a horizontal displacement precision of 4 mm can be achieved.The positioning precision of the GSeisRT regional PPP/PPP-AR is 30%-40%higher than that of the global PPP/PPP-AR.Since 2019,GSeisRT has successfully recorded the static,dynamic,and peak ground displacements for the 2020Oaxaca,Mexico moment magnitude(Mw)7.4 event;the 2020 Lone Pine,California Mw 5.8 event;and the 2021 Qinghai,China Mw 7.3 event in real time.The resulting immediate magnitude estimates have an error of around 0.1 only.The GSeisRT software is open to the scientific community and has been applied by the China Earthquake Ne tworks Center,the EarthScope Consortium of the United States,the National Seismological Center of Chile,Institute of Geological and Nuclear Sciences Limited(GNS Science Te PūAo)of New Zealand,and the Geospatial Information Agency of Indonesia.展开更多
For multi-vehicle networks,Cooperative Positioning(CP)technique has become a promising way to enhance vehicle positioning accuracy.Especially,the CP performance could be further improved by introducing Sensor-Rich Veh...For multi-vehicle networks,Cooperative Positioning(CP)technique has become a promising way to enhance vehicle positioning accuracy.Especially,the CP performance could be further improved by introducing Sensor-Rich Vehicles(SRVs)into CP networks,which is called SRV-aided CP.However,the CP system may split into several sub-clusters that cannot be connected with each other in dense urban environments,in which the sub-clusters with few SRVs will suffer from degradation of CP performance.Since Unmanned Aerial Vehicles(UAVs)have been widely used to aid vehicular communications,we intend to utilize UAVs to assist sub-clusters in CP.In this paper,a UAV-aided CP network is constructed to fully utilize information from SRVs.First,the inter-node connection structure among the UAV and vehicles is designed to share available information from SRVs.After that,the clustering optimization strategy is proposed,in which the UAV cooperates with the high-precision sub-cluster to obtain available information from SRVs,and then broadcasts this positioning-related information to other low-precision sub-clusters.Finally,the Locally-Centralized Factor Graph Optimization(LC-FGO)algorithm is designed to fuse positioning information from cooperators.Simulation results indicate that the positioning accuracy of the CP system could be improved by fully utilizing positioning-related information from SRVs.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
Objective: The present research aims to determine if adherence to the Lewinnek safe zone, when exclusively considered, constitutes a pivotal element for ensuring stability in the context of total hip arthroplasty. Thi...Objective: The present research aims to determine if adherence to the Lewinnek safe zone, when exclusively considered, constitutes a pivotal element for ensuring stability in the context of total hip arthroplasty. This is done by examining the acetabular placement in instances of hip dislocation after total hip arthroplasty (THA). Methodology: The authors searched 2653 patient records from 2015 to 2022 looking for patients who had total hip arthroplasty at our facility. For the analysis, 23 patients were culled from 64 individuals who exhibited post-THA dislocations, employing a stringent exclusion criterion, and the resultant acetabular angulation and anteversion were quantified utilizing PEEKMED software (Peek Health S.A., Portugal) upon radiographic evidence. Results: Within the operational timeframe, from the cohort of 2653 subjects, 64 presented with at least a singular incident of displacement. Post-exclusion criterion enforcement, 23 patients were eligible for inclusion. Of these, 10 patients conformed to the safe zone demarcated by Lewinnek for both inclination and anteversion angles, while 13 exhibited deviations from the prescribed anteversion and/or inclination benchmarks. Conclusion: Analysis of the 23 patients reveals that 13 did not confirm to be in the safe zone parameters for anteversion and/or inclination, whereas 10 were within the safe zone as per Lewinnek’s guidelines. This investigative review, corroborated by extant literature, suggests that the isolated consideration of the Lewinnek safe zone does not suffice as a solitary protective factor. It further posits that additional variables are equally critical as acetabular positioning and mandate individual assessment.展开更多
Surface-enhanced Raman spectroscopy(SERS)has evolved from a laboratory technique to a practical tool for ultra-sensitive detection,particularly in the biomedical field,where precise molecular identification is crucial...Surface-enhanced Raman spectroscopy(SERS)has evolved from a laboratory technique to a practical tool for ultra-sensitive detection,particularly in the biomedical field,where precise molecular identification is crucial.Despite significant advancements,a gap remains in the literature,as no comprehensive review systematically addresses the high-precision construction of SERS substrates for ultrasensitive biomedical detection.This review fills that gap by exploring recent progress in fabricating high-precision SERS substrates,emphasizing their role in enabling ultrasensitive bio-medical sensors.We carefully examine the key to these advancements is the precision engineering of substrates,including noble metals,semiconductors,carbon-based materials,and two-dimensional materials,which is essential for achieving the high sensitivity required for ultrasensitive detection.Applications in biomedical diagnostics and molecular analysis are highlighted.Finally,we address the challenges in SERS substrate preparation and outline future directions,focusing on improvement strategies,design concepts,and expanding applications for these advanced materials.展开更多
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
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
Large-aperture optical components are of paramount importance in domains such as integrated circuits,photolithography,aerospace,and inertial confinement fusion.However,measuring their surface profiles relies predomina...Large-aperture optical components are of paramount importance in domains such as integrated circuits,photolithography,aerospace,and inertial confinement fusion.However,measuring their surface profiles relies predominantly on the phase-shifting approach,which involves collecting multiple interferograms and imposes stringent demands on environmental stability.These issues significantly hinder its ability to achieve real-time and dynamic high-precision measurements.Therefore,this study proposes a high-precision large-aperture single-frame interferometric surface profile measurement(LA-SFISPM)method based on deep learning and explores its capability to realize dynamic measurements with high accuracy.The interferogram is matched to the phase by training the data measured using the small aperture.The consistency of the surface features of the small and large apertures is enhanced via contrast learning and feature-distribution alignment.Hence,high-precision phase reconstruction of large-aperture optical components can be achieved without using a phase shifter.The experimental results show that for the tested mirror withΦ=820 mm,the surface profile obtained from LA-SFISPM is subtracted point-by-point from the ground truth,resulting in a maximum single-point error of 4.56 nm.Meanwhile,the peak-to-valley(PV)value is 0.0758λ,and the simple repeatability of root mean square(SR-RMS)value is 0.00025λ,which aligns well with the measured results obtained by ZYGO.In particular,a significant reduction in the measurement time(reduced by a factor of 48)is achieved compared with that of the traditional phase-shifting method.Our proposed method provides an efficient,rapid,and accurate method for obtaining the surface profiles of optical components with different diameters without employing a phase-shifting approach,which is highly desired in large-aperture interferometric measurement systems.展开更多
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
The elliptic integral method(EIM) is an efficient analytical approach for analyzing large deformations of elastic beams. However, it faces the following challenges.First, the existing EIM can only handle cases with kn...The elliptic integral method(EIM) is an efficient analytical approach for analyzing large deformations of elastic beams. However, it faces the following challenges.First, the existing EIM can only handle cases with known deformation modes. Second,the existing EIM is only applicable to Euler beams, and there is no EIM available for higher-precision Timoshenko and Reissner beams in cases where both force and moment are applied at the end. This paper proposes a general EIM for Reissner beams under arbitrary boundary conditions. On this basis, an analytical equation for determining the sign of the elliptic integral is provided. Based on the equation, we discover a class of elliptic integral piecewise points that are distinct from inflection points. More importantly, we propose an algorithm that automatically calculates the number of inflection points and other piecewise points during the nonlinear solution process, which is crucial for beams with unknown or changing deformation modes.展开更多
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
With the intensifying competition in the integrated circuit(IC)industry,the high turnover rate of integrated circuit engineers has become a prominent issue affecting the technological continuity of high-precision,spec...With the intensifying competition in the integrated circuit(IC)industry,the high turnover rate of integrated circuit engineers has become a prominent issue affecting the technological continuity of high-precision,specialized,and innovative enterprises.As a representative of such enterprises,JL Technology has faced challenges to its R&D efficiency due to talent loss in recent years.This study takes this enterprise as a case to explore feasible paths to reduce turnover rates through optimizing training and career development systems.The research designs a method combining learning maps and talent maps,utilizes a competency model to clarify the direction for engineers’skill improvement,implements talent classification management using a nine-grid model,and achieves personalized training through Individual Development Plans(IDPs).Analysis of the enterprise’s historical data reveals that the main reasons for turnover are unclear career development paths and insufficient resources for skill improvement.After pilot implementation,the turnover rate in core departments decreased by 12%,and employee satisfaction with training increased by 24%.The results indicate that matching systematic talent reviews with dynamic learning resources can effectively enhance engineers’sense of belonging.This study provides a set of highly operational management tools for small and medium-sized high-precision,specialized,and innovative technology enterprises,verifies their applicability in such enterprises,and offers replicable experiences for similar enterprises to optimize their talent strategies[1].展开更多
As global efforts to combat climate change intensify,offshore wind farms have emerged as scalable and sustainable solutions.However,their deployment depends heavily on the availability of specialized vessels with Dyna...As global efforts to combat climate change intensify,offshore wind farms have emerged as scalable and sustainable solutions.However,their deployment depends heavily on the availability of specialized vessels with Dynamic Positioning(DP)systems such as Wind Turbine Installation Vessels(WTIVs)and Service Operation Vessels(SOVs).Despite their importance,long-term demand forecasting for such vessels remains underexplored,especially in South Korea.This study presents the dDP-W model,a System Dynamics(SD)-based framework that simulates the evolving demand for DP vessels under varying technological,policy,and environmental conditions.Unlike conventional methods based on historical extrapolation,the model uses feedback-driven causality and scenario-based simulations aligned with South Korea’s offshore wind roadmap(2026-2036).Three WTIV demand scenarios—baseline,optimistic,and pessimistic—were constructed based on vessel productivity and weather-related downtime.SOV demand was estimated using cumulative turbine counts and fixed vessel coverage ratios.The simulations indicate that WTIV demand peaks in the early 2030s,requiring 6 to 7 vessels depending on conditions,while SOV demand increases steadily,reaching nearly 70 vessels by 2036.These findings highlight the need for early vessel procurement,infrastructure investment,and workforce preparation.By integrating technical,logistical,and policy factors into a dynamic model,this study provides a practical decision-support tool for stakeholders in shipbuilding and offshore energy.The results offer strategic insights to address potential vessel shortages and ensure alignment with national renewable energy goals.展开更多
基金supported by National Natural Science Foundation of China(No.62101298)Collaborative Education Project between Industry and Academia,China(22050609312501)。
文摘60 GHz millimeter wave(mmWave)system provides extremely high time resolution and multipath components(MPC)separation and has great potential to achieve high precision in the indoor positioning.However,the ranging data is often contaminated by non-line-of-sight(NLOS)transmission.First,six features of 60GHz mm Wave signal under LOS and NLOS conditions are evaluated.Next,a classifier constructed by random forest(RF)algorithm is used to identify line-of-sight(LOS)or NLOS channel.The identification mechanism has excellent generalization performance and the classification accuracy is over 97%.Finally,based on the identification results,a residual weighted least squares positioning method is proposed.All ranging information including that under NLOS channels is fully utilized,positioning failure caused by insufficient LOS links can be avoided.Compared with the conventional least squares approach,the positioning error of the proposed algorithm is reduced by 49%.
基金Supported by the Short-wave Infrared Camera Systems(B025F40622024)。
文摘The accuracy of spot centroid positioning has a significant impact on the tracking accuracy of the system and the stability of the laser link construction.In satellite laser communication systems,the use of short-wave infrared wavelengths as beacon light can reduce atmospheric absorption and signal attenuation.However,there are strong non-uniformity and blind pixels in the short-wave infrared image,which makes the image distorted and leads to the decrease of spot centroid positioning accuracy.Therefore,the high-precision localization of the spot centroid of the short-wave infrared images is of great research significance.A high-precision spot centroid positioning model for short-wave infrared is proposed to correct for non-uniformity and blind pixels in short-wave infrared images and quantify the localization errors caused by the two,further model-based localization error simulations are performed,and a novel spot centroid positioning payload for satellite laser communications has been designed using the latest 640×512 planar array InGaAs shortwave infrared detector.The experimental results show that the non-uniformity of the corrected image is reduced from 7%to 0.6%,the blind pixels rejection rate reaches 100%,the frame rate can be up to 2000 Hz,and the spot centroid localization accuracy is as high as 0.1 pixel point,which realizes high-precision spot centroid localization of high-frame-frequency short-wave infrared images.
基金supported by the International S&T Cooperation Program of China(GrantNo.2010DFB43660)National Natural Science Foundation of China(Grant No.51375286)Scientific Research Program Funded by Shaanxi Provincial Education Department(Program No.16JF005)
文摘Traditionally, basis weight control valve is driven by a constant frequency pulse signal. Therefore, it is difficult for the valve to match the control precision of basis weight. Dynamic simulation research using Matlab/Simulink indicates that there is much more overshoot and fluctuating during the valve-positioning process. In order to improve the valve-positioning precision, the control method of trapezoidal velocity curve was studied. The simulation result showed that the positioning steady-state error was less than 0.0056%, whereas the peak error was less than 0.016% by using trapezoidal velocity curve at 10 positioning steps. A valve-positioning precision experimental device for the stepper motor of basis weight control valve was developed. The experiment results showed that the error ratio of 1/10000 positioning steps was 4% by using trapezoidal velocity curve. Furthermore, the error ratio of 10/10000 positioning steps was 0.5%. It proved that the valve-positioning precision of trapezoidal velocity curve was much higher than that of the constant frequency pulse signal control strategy. The new control method of trapezoidal velocity curve can satisfy the precision requirement of 10000 steps.
基金partially sponsored by the National 973 Project of China(2013CB733303)partially supported by the postgraduate independent exploration project of Central South University(2014zzts249)
文摘Selecting the optimal reference satellite is an important component of high-precision relat/ve positioning because the reference satellite directly influences the strength of the normal equation. The reference satellite selection methods based on elevation and positional dilution of precision （PDOP） value were compared. Results show that all the above methods cannot select the optimal reference satellite. We introduce condition number of the design matrix in the reference satellite selection method to improve structure of the normal equation, because condition number can indicate the ill condition of the normal equation. The experimental results show that the new method can improve positioning accuracy and reliability in precise relative positioning.
基金National Key Scientific Instrument and Equipment Development Project(No.2013YQ170539)
文摘Multi-sensor coordinate unification in dimensional metrology is used in order to get holistic, more accurate and reliable information about a workpiece based on several or multiple measurement values from one or more sensors. Because of the problem that standard ball is deficient as a standard artifact in the coordinate unification of high-precision composite measurement in two dimensions （2D） , a new method is proposed in this paper which uses angle gauge blocks as standard artifacts to achieve coordinate unification between the image sensor and the tactile probe. By comparing the standard ball with the angle gauge block as a standard artifact, theoretical analysis and experimental results are given to prove that it is more precise and more convenient to use angle gauge blocks as standard artifacts to achieve coordinate unification of high-precision composite measurement in two dimensions.
基金National Natural Science Foundation of China(No.12472038)Natural Science Foundation of Jiangsu Province(No.BK20230688)+2 种基金Natural Science Foundation of the Jiangsu Higher Education Institutions of China(No.22KJB440004)Key Research and Development Program of Xuzhou(No.KC22404)Research Fund for Doctoral Degree Teachers of Jiangsu Normal University of China(No.22XFRS011).
文摘A rock-drilling jumbo is the main piece of tunneling equipment used in the energy and infrastructure industries in various countries.The positioning accuracy of its drilling boom greatly affects tunneling efficiency and section-forming quality of mine roadways and engineering tunnels.In order to improve the drilling-positioning accuracy of a three-boom drilling jumbo,we established a kinematics model of the multi-degree-of-freedom(multi-DOF)multi-boom system,using the improved Denavit-Hartenberg(D-H)method,and obtained the mapping relationship between the end position and the amount of motion of each joint.The error of the inverse kinematics calculation for the drilling boom is estimated by an analytical method and a global search algorithm based on particle swarm optimization(PSO)for a straight blasting hole and an inclined blasting hole.On this basis,we propose a back-propagation(BP)neural network optimized by an improved sparrow search algorithm(ISSA)to predict the positioning error of the drilling booms of a three-boom drilling jumbo.In order to verify the accuracy of the proposed error compensation model,we built an automatic-control test platform for the boom,and carried out a positioning error compensation test on the boom.The results show that the average drilling-positioning error was reduced from 9.79 to 5.92 cm,and the error was reduced by 39.5%.Therefore,the proposed method effectively reduces the positioning error of the drilling boom,and improves the accuracy and efficiency of rock drilling.
基金supported by the National Natural Science Foundation of China(42274039)Shaanxi Provincial Innovation Capacity Support Plan Project(2023KJXX-050)+2 种基金The Open Grants of the State Key Laboratory of Severe Weather(2023LASW-B18)Scientific and technological research projects for major issues in military medicine and aviation medicine(2022ZZXM012)Local special scientific research plan project of Shaanxi Provincial Department of Education(22JE012)。
文摘Zenith Tropospheric Delay(ZTD)is an important factor that restricts the high-precision positioning of global navigation satellite system(GNSS),and it is of great significance in establishing a real-time and highprecision ZTD model.However,existing ZTD models only consider the impact of linear terms on ZTD estimation,whereas the nonlinear factors have rarely been investigated before and thus become the focus of this study.A real-time and high-precision ZTD model for large height difference area is proposed by considering the linear and nonlinear characteristics of ZTD spatiotemporal variations and is called the realtime linear and nonlinearity ZTD(RLNZ)model.This model uses the ZTD estimated from the Global Pressure and Temperature 3(GPT3)model as the initial value.The linear impacts of periodic term and height on the estimation of ZTD difference between GNSS and GPT3 model are first considered.In addition,nonlinear factors such as geographical location and time are further used to fit the remaining nonlinear ZTD residuals using the general regression neural network method.Finally,the RLNZ-derived ZTD is obtained at an arbitrary location.The western United States,with height difference ranging from-500 to 4000 m,is selected,and the hourly ZTD of 484 GNSS stations provided by the Nevada Geodetic Laboratory(NGL)and the data of 9 radiosonde(RS)stations in the year 2021 are used.Experiment results show that a better performance of ZTD estimation can be retrieved from the proposed RLNZ model when compared with the GPT3 model.Statistical results show the averaged root mean square(RMS),Bias,and mean absolute error(MAE)of ZTD from GPT3 and RLNZ models are 33.7/0.8/25.7 mm and 22.6/0.1/17.4 mm,respectively.The average improvement rate of the RLNZ model is 33% when compared to the GPT3 model.Finally,the application of the proposed RLNZ model in simulated real-time Precise Point Positioning(PPP)indicates that the accuracy of PPP in N,E and U components is improved by 8%,2%,and 6% when compared with that from the GPT3-based PPP.Meanwhile,the convergence time in N and U components is improved by 23% and 7%,respectively.Such results verify the superiority of the proposed RLNZ model in retrieving realtime ZTD maps for GNSS positioning and navigation applications.
基金funded by National Science Foundation of China(42025401)National Key Research and Development Program of China(2022YFB3903800)。
文摘Precise coseismic displacements in earthquake/tsunamic early warning are necessary to characterize earthquakes in real time in order to enable decision-makers to issue alerts for public safety.Real-time global navigation satellite systems(GNSSs)have been a valuable tool in monitoring seismic motions,allowing permanent displacement computation to be unambiguously achieved.As a valuable tool presented to the seismic commu nity,the GSeisRT software developed by Wuhan University(China)can realize multi-GNSS precise point positioning with ambiguity resolution(PPP-AR)and achieve centimeterlevel to sub-centimeter-level precision in real time.While the stable maintenance of a global precise point positioning(PPP)service is challenging,this software is capable of estimating satellite clocks and phase biases in real time using a regional GNSS network.This capability makes GSeisRT especially suitable for proprietary GNSS networks and,more importantly,the highest possible positio ning precision and reliability can be obtained.According to real-time results from the Network of the Americas,the mean root mean square(RMS)errors of kinematic PPP-AR over a 24 h span are as low as 1.2,1.3,and 3.0 cm in the east,north,and up components,respectively.Within the few minutes that span a typical seismic event,a horizontal displacement precision of 4 mm can be achieved.The positioning precision of the GSeisRT regional PPP/PPP-AR is 30%-40%higher than that of the global PPP/PPP-AR.Since 2019,GSeisRT has successfully recorded the static,dynamic,and peak ground displacements for the 2020Oaxaca,Mexico moment magnitude(Mw)7.4 event;the 2020 Lone Pine,California Mw 5.8 event;and the 2021 Qinghai,China Mw 7.3 event in real time.The resulting immediate magnitude estimates have an error of around 0.1 only.The GSeisRT software is open to the scientific community and has been applied by the China Earthquake Ne tworks Center,the EarthScope Consortium of the United States,the National Seismological Center of Chile,Institute of Geological and Nuclear Sciences Limited(GNS Science Te PūAo)of New Zealand,and the Geospatial Information Agency of Indonesia.
基金supported by the National Natural Science Foundation of China(No.62271399)the National Key Research and Development Program of China(No.2022YFB1807102)。
文摘For multi-vehicle networks,Cooperative Positioning(CP)technique has become a promising way to enhance vehicle positioning accuracy.Especially,the CP performance could be further improved by introducing Sensor-Rich Vehicles(SRVs)into CP networks,which is called SRV-aided CP.However,the CP system may split into several sub-clusters that cannot be connected with each other in dense urban environments,in which the sub-clusters with few SRVs will suffer from degradation of CP performance.Since Unmanned Aerial Vehicles(UAVs)have been widely used to aid vehicular communications,we intend to utilize UAVs to assist sub-clusters in CP.In this paper,a UAV-aided CP network is constructed to fully utilize information from SRVs.First,the inter-node connection structure among the UAV and vehicles is designed to share available information from SRVs.After that,the clustering optimization strategy is proposed,in which the UAV cooperates with the high-precision sub-cluster to obtain available information from SRVs,and then broadcasts this positioning-related information to other low-precision sub-clusters.Finally,the Locally-Centralized Factor Graph Optimization(LC-FGO)algorithm is designed to fuse positioning information from cooperators.Simulation results indicate that the positioning accuracy of the CP system could be improved by fully utilizing positioning-related information from SRVs.
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.
文摘Objective: The present research aims to determine if adherence to the Lewinnek safe zone, when exclusively considered, constitutes a pivotal element for ensuring stability in the context of total hip arthroplasty. This is done by examining the acetabular placement in instances of hip dislocation after total hip arthroplasty (THA). Methodology: The authors searched 2653 patient records from 2015 to 2022 looking for patients who had total hip arthroplasty at our facility. For the analysis, 23 patients were culled from 64 individuals who exhibited post-THA dislocations, employing a stringent exclusion criterion, and the resultant acetabular angulation and anteversion were quantified utilizing PEEKMED software (Peek Health S.A., Portugal) upon radiographic evidence. Results: Within the operational timeframe, from the cohort of 2653 subjects, 64 presented with at least a singular incident of displacement. Post-exclusion criterion enforcement, 23 patients were eligible for inclusion. Of these, 10 patients conformed to the safe zone demarcated by Lewinnek for both inclination and anteversion angles, while 13 exhibited deviations from the prescribed anteversion and/or inclination benchmarks. Conclusion: Analysis of the 23 patients reveals that 13 did not confirm to be in the safe zone parameters for anteversion and/or inclination, whereas 10 were within the safe zone as per Lewinnek’s guidelines. This investigative review, corroborated by extant literature, suggests that the isolated consideration of the Lewinnek safe zone does not suffice as a solitary protective factor. It further posits that additional variables are equally critical as acetabular positioning and mandate individual assessment.
基金supported by the projects funded by the Education Department of Shaanxi Provincial Government(NO.23JP116)the Natural Science Fund of Shaanxi Province(NO.2024JC-YBMS-396)+3 种基金the National Natural Science Foundation of China(NO.52171191,52371198,U22A20137)the Constructing National Independent Innovation Demonstration Zones(XM2024XTGXQ05)Shenzhen Science and Technology Innovation Program(JCYJ20220818102215033,GJHZ20210705142542015,JCYJ20220530160811027)Guangdong HUST Industrial Technology Research Institute,Guangdong Provincial Key Laboratory of Manufacturing Equipment Digitization(2023B1212060012).
文摘Surface-enhanced Raman spectroscopy(SERS)has evolved from a laboratory technique to a practical tool for ultra-sensitive detection,particularly in the biomedical field,where precise molecular identification is crucial.Despite significant advancements,a gap remains in the literature,as no comprehensive review systematically addresses the high-precision construction of SERS substrates for ultrasensitive biomedical detection.This review fills that gap by exploring recent progress in fabricating high-precision SERS substrates,emphasizing their role in enabling ultrasensitive bio-medical sensors.We carefully examine the key to these advancements is the precision engineering of substrates,including noble metals,semiconductors,carbon-based materials,and two-dimensional materials,which is essential for achieving the high sensitivity required for ultrasensitive detection.Applications in biomedical diagnostics and molecular analysis are highlighted.Finally,we address the challenges in SERS substrate preparation and outline future directions,focusing on improvement strategies,design concepts,and expanding applications for these advanced materials.
基金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 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funded by the National Natural Science Foundation of China Instrumentation Program(52327806)Youth Fund of the National Nature Foundation of China(62405020)China Postdoctoral Science Foundation(2024M764131).
文摘Large-aperture optical components are of paramount importance in domains such as integrated circuits,photolithography,aerospace,and inertial confinement fusion.However,measuring their surface profiles relies predominantly on the phase-shifting approach,which involves collecting multiple interferograms and imposes stringent demands on environmental stability.These issues significantly hinder its ability to achieve real-time and dynamic high-precision measurements.Therefore,this study proposes a high-precision large-aperture single-frame interferometric surface profile measurement(LA-SFISPM)method based on deep learning and explores its capability to realize dynamic measurements with high accuracy.The interferogram is matched to the phase by training the data measured using the small aperture.The consistency of the surface features of the small and large apertures is enhanced via contrast learning and feature-distribution alignment.Hence,high-precision phase reconstruction of large-aperture optical components can be achieved without using a phase shifter.The experimental results show that for the tested mirror withΦ=820 mm,the surface profile obtained from LA-SFISPM is subtracted point-by-point from the ground truth,resulting in a maximum single-point error of 4.56 nm.Meanwhile,the peak-to-valley(PV)value is 0.0758λ,and the simple repeatability of root mean square(SR-RMS)value is 0.00025λ,which aligns well with the measured results obtained by ZYGO.In particular,a significant reduction in the measurement time(reduced by a factor of 48)is achieved compared with that of the traditional phase-shifting method.Our proposed method provides an efficient,rapid,and accurate method for obtaining the surface profiles of optical components with different diameters without employing a phase-shifting approach,which is highly desired in large-aperture interferometric measurement systems.
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 by the National Natural Science Foundation of China (Nos. 12172388 and 12472400)the Guangdong Basic and Applied Basic Research Foundation of China(No. 2025A1515011975)the Scientific Research Project of Guangdong Polytechnic Normal University of China (No. 2023SDKYA010)
文摘The elliptic integral method(EIM) is an efficient analytical approach for analyzing large deformations of elastic beams. However, it faces the following challenges.First, the existing EIM can only handle cases with known deformation modes. Second,the existing EIM is only applicable to Euler beams, and there is no EIM available for higher-precision Timoshenko and Reissner beams in cases where both force and moment are applied at the end. This paper proposes a general EIM for Reissner beams under arbitrary boundary conditions. On this basis, an analytical equation for determining the sign of the elliptic integral is provided. Based on the equation, we discover a class of elliptic integral piecewise points that are distinct from inflection points. More importantly, we propose an algorithm that automatically calculates the number of inflection points and other piecewise points during the nonlinear solution process, which is crucial for beams with unknown or changing deformation modes.
基金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With the intensifying competition in the integrated circuit(IC)industry,the high turnover rate of integrated circuit engineers has become a prominent issue affecting the technological continuity of high-precision,specialized,and innovative enterprises.As a representative of such enterprises,JL Technology has faced challenges to its R&D efficiency due to talent loss in recent years.This study takes this enterprise as a case to explore feasible paths to reduce turnover rates through optimizing training and career development systems.The research designs a method combining learning maps and talent maps,utilizes a competency model to clarify the direction for engineers’skill improvement,implements talent classification management using a nine-grid model,and achieves personalized training through Individual Development Plans(IDPs).Analysis of the enterprise’s historical data reveals that the main reasons for turnover are unclear career development paths and insufficient resources for skill improvement.After pilot implementation,the turnover rate in core departments decreased by 12%,and employee satisfaction with training increased by 24%.The results indicate that matching systematic talent reviews with dynamic learning resources can effectively enhance engineers’sense of belonging.This study provides a set of highly operational management tools for small and medium-sized high-precision,specialized,and innovative technology enterprises,verifies their applicability in such enterprises,and offers replicable experiences for similar enterprises to optimize their talent strategies[1].
文摘As global efforts to combat climate change intensify,offshore wind farms have emerged as scalable and sustainable solutions.However,their deployment depends heavily on the availability of specialized vessels with Dynamic Positioning(DP)systems such as Wind Turbine Installation Vessels(WTIVs)and Service Operation Vessels(SOVs).Despite their importance,long-term demand forecasting for such vessels remains underexplored,especially in South Korea.This study presents the dDP-W model,a System Dynamics(SD)-based framework that simulates the evolving demand for DP vessels under varying technological,policy,and environmental conditions.Unlike conventional methods based on historical extrapolation,the model uses feedback-driven causality and scenario-based simulations aligned with South Korea’s offshore wind roadmap(2026-2036).Three WTIV demand scenarios—baseline,optimistic,and pessimistic—were constructed based on vessel productivity and weather-related downtime.SOV demand was estimated using cumulative turbine counts and fixed vessel coverage ratios.The simulations indicate that WTIV demand peaks in the early 2030s,requiring 6 to 7 vessels depending on conditions,while SOV demand increases steadily,reaching nearly 70 vessels by 2036.These findings highlight the need for early vessel procurement,infrastructure investment,and workforce preparation.By integrating technical,logistical,and policy factors into a dynamic model,this study provides a practical decision-support tool for stakeholders in shipbuilding and offshore energy.The results offer strategic insights to address potential vessel shortages and ensure alignment with national renewable energy goals.
