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
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
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
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 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
Intertrochanteric fractures,prevalent among older adults,pose significant clinical challenges due to high morbidity,mortality,and complication rates.Despite advancements in surgical methods and implant technology,one-...Intertrochanteric fractures,prevalent among older adults,pose significant clinical challenges due to high morbidity,mortality,and complication rates.Despite advancements in surgical methods and implant technology,one-year mortality remains between 20%and 30%,with up to 20%of survivors requiring revision surgery due to mechanical complications.Accurate fracture reduction and precise implant positioning are critical determinants of successful outcomes.This review synthesizes current literature on key radiographic parameters essential for evaluating fracture reduction quality and implant placement in intertrochanteric fracture fixation.Standardized intraoperative imaging techniques,such as correct anteroposterior and lateral fluoroscopic views,are fundamental for identifying malalignment.Important radiographic measures include the neck shaft angle,greater trochanter orthogonal line,anterior cortical line,and calcar displacement assessment.Reduction quality indices,notably the Baumgaertner and Chang Reduction Quality Criteria,provide reliable frameworks for predicting mechanical complications.Additionally,implant positioning parameters—including tip-apex distance,Calcar-referenced tip-apex distance,Cleveland zones,and Parker’s ratio index—are discussed as predictors of mechanical complications.Enhanced understanding and application of these radiographic criteria can improve surgical precision,reduce complications,and ultimately optimize patient outcomes in intertrochanteric fracture management.展开更多
The impact of location services on people’s lives has grown significantly in the era of widespread smart device usage.Due to global navigation satellite system(GNSS)signal rejection,weak signal strength in indoor env...The impact of location services on people’s lives has grown significantly in the era of widespread smart device usage.Due to global navigation satellite system(GNSS)signal rejection,weak signal strength in indoor environments and radio signal interference caused by multiwall environments,which collectively lead to significant positioning errors,vision-based positioning has emerged as a crucial method in indoor positioning research.This paper introduces a scale hierarchical matching model to tackle challenges associated with large visual databases and high scene similarity,both of which will compromise matching accuracy and lead to prolonged positioning delays.The proposed model establishes an image feature database using GIST features and speeded up robust feature(SURF)in the offline stage.In the online stage,a positioning navigating algorithm is constructed based on Dijkstra’s path planning.Additionally,a corresponding Android application has been developed to facilitate visual positioning and navigation in indoor environments.Experimental results obtained in real indoor environments demonstrate that the proposed method significantly enhances positioning accuracy compared with similar algorithms,while effectively reducing time overhead.This improvement caters to the requirements for indoor positioning and navigation,thereby meeting user needs.展开更多
In order to solve the problem of limited computational resources of multi-unmanned systems airborne navigation platform,a distributed cooperative positioning method based on confidence evaluation is proposed.Firstly,t...In order to solve the problem of limited computational resources of multi-unmanned systems airborne navigation platform,a distributed cooperative positioning method based on confidence evaluation is proposed.Firstly,the impact of ranging error,priori information,spatial geometric configuration and adjacent nodes count on cooperative positioning performance are analyzed individually.Secondly,a confidence evaluation method for measurement information of adjacent nodes is designed according to the cooperative positioning principle,which comprehensively considers the coupling relationship between influencing factors.Finally,a distributed cooperative navigation filter based on inter-vehicle ranging is designed.Simulation studies show that confidence evaluation method proposed in this paper can effectively characterize the contribution of measurement information to positioning results,and positioning accuracy under the proposed method is improved by more than 15%compared with the traditional screening methods based on optimal geometric configuration and closest distance.展开更多
Global Navigation Satellite Systems(GNSSs)are vulnerable to both unintentional interference and intentional attacks,making it difficult to meet the stringent safety requirements of railway train control systems.The gr...Global Navigation Satellite Systems(GNSSs)are vulnerable to both unintentional interference and intentional attacks,making it difficult to meet the stringent safety requirements of railway train control systems.The growing threat to information security posed by spoofing attacks has received limited attention.This study investigates the impact of GNSS spoofing attacks on train positioning,emphasizing their detrimental effects on the accuracy and availability of train location report functions for train operation control.To explore the antispoofing performance of typical GNSS-based train positioning schemes,specific approaches,and system architectures are designed under two GNSS-alone and two GNSS-integrated train positioning schemes.Field data are utilized to establish spoofing attack scenarios for GNSS-based train positioning,with which the anti-spoofing capabilities of different train positioning schemes are evaluated.Experimental results indicate that under specific conditions,the GNSS-integrated positioning schemes demonstrate superior GNSS spoofing suppression capabilities.Results of the tests present valuable guidance for designers and manufacturers in developing more advanced and resilient train positioning solutions and equipment for the next generation of train control systems,thereby promoting the applications of GNSS technology in railway systems.展开更多
In order to solve the problem that the star point positioning accuracy of the star sensor in near space is decreased due to atmospheric background stray light and rapid maneuvering of platform, this paper proposes a s...In order to solve the problem that the star point positioning accuracy of the star sensor in near space is decreased due to atmospheric background stray light and rapid maneuvering of platform, this paper proposes a star point positioning algorithm based on the capsule network whose input and output are both vectors. First, a PCTL (Probability-Coordinate Transformation Layer) is designed to represent the mapping relationship between the probability output of the capsule network and the star point sub-pixel coordinates. Then, Coordconv Layer is introduced to implement explicit encoding of space information and the probability is used as the centroid weight to achieve the conversion between probability and star point sub-pixel coordinates, which improves the network’s ability to perceive star point positions. Finally, based on the dynamic imaging principle of star sensors and the characteristics of near-space environment, a star map dataset for algorithm training and testing is constructed. The simulation results show that the proposed algorithm reduces the MAE (Mean Absolute Error) and RMSE (Root Mean Square Error) of the star point positioning by 36.1% and 41.7% respectively compared with the traditional algorithm. The research results can provide important theory and technical support for the scheme design, index demonstration, test and evaluation of large dynamic star sensors in near space.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
Spatio-temporal variation of sound speed,in seafloor geodetic precise positioning,can always be attributed to the time error.Firstly,this paper analyzes the existing error compensation model,i.e.,the time ratio model,...Spatio-temporal variation of sound speed,in seafloor geodetic precise positioning,can always be attributed to the time error.Firstly,this paper analyzes the existing error compensation model,i.e.,the time ratio model,which is expressed by the recorded time multiplying a ratio coefficient.And then a time split model is proposed by expressing the acoustic ray traveling time as the recorded time pluses a perturbation time error.The theoretical differences between the proposed time bias compensation model and the time ratio model are analyzed.Under the new framework,sound speed perturbation models with optimal single-layer spatial gradient and multi-layer spatial gradients are developed to compensate for sound speed error in the complex cases.Numerical computation shows that the simple time split model keeps the same accuracy as some complicated models while considering the distribution of random error.Furthermore,multi-layer model can improve the positioning accuracy without putting the pressure on parametrization.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
Rail positioning is a critical step for detecting rail defects downstream.However,existing orientation-based detectors struggle to effectively manage rails with arbitrary inclinations and high aspect ratios,particular...Rail positioning is a critical step for detecting rail defects downstream.However,existing orientation-based detectors struggle to effectively manage rails with arbitrary inclinations and high aspect ratios,particularly in turnout sections.To address these challenges,a fuzzy boundary guidance and oriented Gaussian function-based anchor-free network termed the rail positioning network(RP-Net)is proposed for rail positioning in turnout sections.First,an oriented Gaussian function-based label generation strategy is introduced.This strategy produces smoother and more accu-rate label values by accounting for the specific aspect ratios and orientations of the rails.Second,a fuzzy boundary learning module is developed to enhance the network’s abil-ity to model the rail boundary regions effectively.Further-more,a boundary guidance module is developed to direct the network in fusing the features obtained from the downs-ampled network output with the boundary region features,which have been enhanced to contain more refined posi-tional and structural information.A local channel attention mechanism is integrated into this module to identify critical channels.Finally,experiments conducted on the tracking dataset show that the proposed RP-Net achieves high posi-tioning accuracy and demonstrates strong adaptability in complex scenarios.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
The single-point bending method,based on atomic force microscopy(AFM),has been extensively validated for characterizing the structural mechanical properties of micro-and nanobeams.Nevertheless,the influence of AFM pro...The single-point bending method,based on atomic force microscopy(AFM),has been extensively validated for characterizing the structural mechanical properties of micro-and nanobeams.Nevertheless,the influence of AFM probe loading and positioning has yet to be subjected to comprehensive investigation.This paper proposes a novel bending-test method based on sequential loading points,in which a series of evenly distributed loads are applied along the length of the central axis on the upper surface of the cantilever.The preliminary measured values of Young’s modulus for an unknown alloy material were 193,178,and 176 GPa,exhibiting a considerable degree of dispersion.An algorithm for self-correction of the positioning error was developed,and this resulted in a positioning error of 53 nm and a final converged Young’s modulus of 161 GPa.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
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
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 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 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(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 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 Orthopaedic Research Foundation of Western Australia,Freie Akademische Gesellschaft Baseland Swiss Orthopaedics.
文摘Intertrochanteric fractures,prevalent among older adults,pose significant clinical challenges due to high morbidity,mortality,and complication rates.Despite advancements in surgical methods and implant technology,one-year mortality remains between 20%and 30%,with up to 20%of survivors requiring revision surgery due to mechanical complications.Accurate fracture reduction and precise implant positioning are critical determinants of successful outcomes.This review synthesizes current literature on key radiographic parameters essential for evaluating fracture reduction quality and implant placement in intertrochanteric fracture fixation.Standardized intraoperative imaging techniques,such as correct anteroposterior and lateral fluoroscopic views,are fundamental for identifying malalignment.Important radiographic measures include the neck shaft angle,greater trochanter orthogonal line,anterior cortical line,and calcar displacement assessment.Reduction quality indices,notably the Baumgaertner and Chang Reduction Quality Criteria,provide reliable frameworks for predicting mechanical complications.Additionally,implant positioning parameters—including tip-apex distance,Calcar-referenced tip-apex distance,Cleveland zones,and Parker’s ratio index—are discussed as predictors of mechanical complications.Enhanced understanding and application of these radiographic criteria can improve surgical precision,reduce complications,and ultimately optimize patient outcomes in intertrochanteric fracture management.
基金Supported by the National Natural Science Foundation of China(No.61971162,61771186)the Natural Science Foundation of Heilongjiang Province(No.PL2024F025)+1 种基金the Open Research Fund of National Mobile Communications Research Laboratory in Southeast University(No.2023D07)the Fundamental Scientific Research Funds of Heilongjiang Province(No.2022-KYYWF-1050).
文摘The impact of location services on people’s lives has grown significantly in the era of widespread smart device usage.Due to global navigation satellite system(GNSS)signal rejection,weak signal strength in indoor environments and radio signal interference caused by multiwall environments,which collectively lead to significant positioning errors,vision-based positioning has emerged as a crucial method in indoor positioning research.This paper introduces a scale hierarchical matching model to tackle challenges associated with large visual databases and high scene similarity,both of which will compromise matching accuracy and lead to prolonged positioning delays.The proposed model establishes an image feature database using GIST features and speeded up robust feature(SURF)in the offline stage.In the online stage,a positioning navigating algorithm is constructed based on Dijkstra’s path planning.Additionally,a corresponding Android application has been developed to facilitate visual positioning and navigation in indoor environments.Experimental results obtained in real indoor environments demonstrate that the proposed method significantly enhances positioning accuracy compared with similar algorithms,while effectively reducing time overhead.This improvement caters to the requirements for indoor positioning and navigation,thereby meeting user needs.
基金supported in part by National Natural Science Foundation of China(Nos.62073163,62103285,62203228)National Defense Basic Research Program(No.JCKY2020605C009)+1 种基金Aeronautic Science Foundation of China(Nos.ASFC-2020Z071052001,202055052003)Foundation Strengthening Program Technology 173 Field Fund(No.2021-JCJQ-JJ-0308)。
文摘In order to solve the problem of limited computational resources of multi-unmanned systems airborne navigation platform,a distributed cooperative positioning method based on confidence evaluation is proposed.Firstly,the impact of ranging error,priori information,spatial geometric configuration and adjacent nodes count on cooperative positioning performance are analyzed individually.Secondly,a confidence evaluation method for measurement information of adjacent nodes is designed according to the cooperative positioning principle,which comprehensively considers the coupling relationship between influencing factors.Finally,a distributed cooperative navigation filter based on inter-vehicle ranging is designed.Simulation studies show that confidence evaluation method proposed in this paper can effectively characterize the contribution of measurement information to positioning results,and positioning accuracy under the proposed method is improved by more than 15%compared with the traditional screening methods based on optimal geometric configuration and closest distance.
基金the National Key Research and Development Program of China(2023YFB3907300)the National Natural Science Foundation of China(U2268206,T2222015)the Beijing Natural Science Foundation(4232031).
文摘Global Navigation Satellite Systems(GNSSs)are vulnerable to both unintentional interference and intentional attacks,making it difficult to meet the stringent safety requirements of railway train control systems.The growing threat to information security posed by spoofing attacks has received limited attention.This study investigates the impact of GNSS spoofing attacks on train positioning,emphasizing their detrimental effects on the accuracy and availability of train location report functions for train operation control.To explore the antispoofing performance of typical GNSS-based train positioning schemes,specific approaches,and system architectures are designed under two GNSS-alone and two GNSS-integrated train positioning schemes.Field data are utilized to establish spoofing attack scenarios for GNSS-based train positioning,with which the anti-spoofing capabilities of different train positioning schemes are evaluated.Experimental results indicate that under specific conditions,the GNSS-integrated positioning schemes demonstrate superior GNSS spoofing suppression capabilities.Results of the tests present valuable guidance for designers and manufacturers in developing more advanced and resilient train positioning solutions and equipment for the next generation of train control systems,thereby promoting the applications of GNSS technology in railway systems.
文摘In order to solve the problem that the star point positioning accuracy of the star sensor in near space is decreased due to atmospheric background stray light and rapid maneuvering of platform, this paper proposes a star point positioning algorithm based on the capsule network whose input and output are both vectors. First, a PCTL (Probability-Coordinate Transformation Layer) is designed to represent the mapping relationship between the probability output of the capsule network and the star point sub-pixel coordinates. Then, Coordconv Layer is introduced to implement explicit encoding of space information and the probability is used as the centroid weight to achieve the conversion between probability and star point sub-pixel coordinates, which improves the network’s ability to perceive star point positions. Finally, based on the dynamic imaging principle of star sensors and the characteristics of near-space environment, a star map dataset for algorithm training and testing is constructed. The simulation results show that the proposed algorithm reduces the MAE (Mean Absolute Error) and RMSE (Root Mean Square Error) of the star point positioning by 36.1% and 41.7% respectively compared with the traditional algorithm. The research results can provide important theory and technical support for the scheme design, index demonstration, test and evaluation of large dynamic star sensors in near space.
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 under contract No.41931076the National Center for Basic Sciences Project under contract No.42388102the Laoshan Laboratory under contract No.LSKJ202205100.
文摘Spatio-temporal variation of sound speed,in seafloor geodetic precise positioning,can always be attributed to the time error.Firstly,this paper analyzes the existing error compensation model,i.e.,the time ratio model,which is expressed by the recorded time multiplying a ratio coefficient.And then a time split model is proposed by expressing the acoustic ray traveling time as the recorded time pluses a perturbation time error.The theoretical differences between the proposed time bias compensation model and the time ratio model are analyzed.Under the new framework,sound speed perturbation models with optimal single-layer spatial gradient and multi-layer spatial gradients are developed to compensate for sound speed error in the complex cases.Numerical computation shows that the simple time split model keeps the same accuracy as some complicated models while considering the distribution of random error.Furthermore,multi-layer model can improve the positioning accuracy without putting the pressure on parametrization.
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Major Scientific Research Projects of China Railway Group(No.K2019G046)the National Key Research and Devel-opment Program of China(No.2020YFB1600700).
文摘Rail positioning is a critical step for detecting rail defects downstream.However,existing orientation-based detectors struggle to effectively manage rails with arbitrary inclinations and high aspect ratios,particularly in turnout sections.To address these challenges,a fuzzy boundary guidance and oriented Gaussian function-based anchor-free network termed the rail positioning network(RP-Net)is proposed for rail positioning in turnout sections.First,an oriented Gaussian function-based label generation strategy is introduced.This strategy produces smoother and more accu-rate label values by accounting for the specific aspect ratios and orientations of the rails.Second,a fuzzy boundary learning module is developed to enhance the network’s abil-ity to model the rail boundary regions effectively.Further-more,a boundary guidance module is developed to direct the network in fusing the features obtained from the downs-ampled network output with the boundary region features,which have been enhanced to contain more refined posi-tional and structural information.A local channel attention mechanism is integrated into this module to identify critical channels.Finally,experiments conducted on the tracking dataset show that the proposed RP-Net achieves high posi-tioning accuracy and demonstrates strong adaptability in complex scenarios.
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.
文摘The single-point bending method,based on atomic force microscopy(AFM),has been extensively validated for characterizing the structural mechanical properties of micro-and nanobeams.Nevertheless,the influence of AFM probe loading and positioning has yet to be subjected to comprehensive investigation.This paper proposes a novel bending-test method based on sequential loading points,in which a series of evenly distributed loads are applied along the length of the central axis on the upper surface of the cantilever.The preliminary measured values of Young’s modulus for an unknown alloy material were 193,178,and 176 GPa,exhibiting a considerable degree of dispersion.An algorithm for self-correction of the positioning error was developed,and this resulted in a positioning error of 53 nm and a final converged Young’s modulus of 161 GPa.
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.
