In this paper,an improved spatio-temporal alignment measurement method is presented to address the inertial matching measurement of hull deformation under the coexistence of time delay and large misalignment angle.Lar...In this paper,an improved spatio-temporal alignment measurement method is presented to address the inertial matching measurement of hull deformation under the coexistence of time delay and large misalignment angle.Large misalignment angle and time delay often occur simultaneously and bring great challenges to the accurate measurement of hull deformation in space and time.The proposed method utilizes coarse alignment with large misalignment angle and time delay estimation of inertial measurement unit modeling to establish a brand-new spatiotemporal aligned hull deformation measurement model.In addition,two-step loop control is designed to ensure the accurate description of dynamic deformation angle and static deformation angle by the time-space alignment method of hull deformation.The experiments illustrate that the proposed method can effectively measure the hull deformation angle when time delay and large misalignment angle coexist.展开更多
High speed photography technique is potentially the most effective way to measure the motion parameter of warhead fragment benefiting from its advantages of high accuracy,high resolution and high efficiency.However,it...High speed photography technique is potentially the most effective way to measure the motion parameter of warhead fragment benefiting from its advantages of high accuracy,high resolution and high efficiency.However,it faces challenge in dense objects tracking and 3D trajectories reconstruction due to the characteristics of small size and dense distribution of fragment swarm.To address these challenges,this work presents a warhead fragments motion trajectories tracking and spatio-temporal distribution reconstruction method based on high-speed stereo photography.Firstly,background difference algorithm is utilized to extract the center and area of each fragment in the image sequence.Subsequently,a multi-object tracking(MOT)algorithm using Kalman filtering and Hungarian optimal assignment is developed to realize real-time and robust trajectories tracking of fragment swarm.To reconstruct 3D motion trajectories,a global stereo trajectories matching strategy is presented,which takes advantages of epipolar constraint and continuity constraint to correctly retrieve stereo correspondence followed by 3D trajectories refinement using polynomial fitting.Finally,the simulation and experimental results demonstrate that the proposed method can accurately track the motion trajectories and reconstruct the spatio-temporal distribution of 1.0×10^(3)fragments in a field of view(FOV)of 3.2 m×2.5 m,and the accuracy of the velocity estimation can achieve 98.6%.展开更多
To solve the problem of target damage assessment when fragments attack target under uncertain projectile and target intersection in an air defense intercept,this paper proposes a method for calculating target damage p...To solve the problem of target damage assessment when fragments attack target under uncertain projectile and target intersection in an air defense intercept,this paper proposes a method for calculating target damage probability leveraging spatio-temporal finite multilayer fragments distribution and the target damage assessment algorithm based on cloud model theory.Drawing on the spatial dispersion characteristics of fragments of projectile proximity explosion,we divide into a finite number of fragments distribution planes based on the time series in space,set up a fragment layer dispersion model grounded in the time series and intersection criterion for determining the effective penetration of each layer of fragments into the target.Building on the precondition that the multilayer fragments of the time series effectively assail the target,we also establish the damage criterion of the perforation and penetration damage and deduce the damage probability calculation model.Taking the damage probability of the fragment layer in the spatio-temporal sequence to the target as the input state variable,we introduce cloud model theory to research the target damage assessment method.Combining the equivalent simulation experiment,the scientific and rational nature of the proposed method were validated through quantitative calculations and comparative analysis.展开更多
To study the mechanism of rockburst and its spatio-temporal evolution criterion,a rockburst simulation experiment was performed on granite specimens,each with a prefabricated circular hole,under different lateral load...To study the mechanism of rockburst and its spatio-temporal evolution criterion,a rockburst simulation experiment was performed on granite specimens,each with a prefabricated circular hole,under different lateral loads.Using micro camera,acoustic emission(AE)system,and infrared thermal imager,the AE characteristics and thermal radiation temperature migration were studied during the rockburst process.Then,the failure mode and damage evolution of the surrounding rock were analyzed.The results demonstrate that increasing the lateral load can first increase and then reduce the bearing capacity of the hole.In this experiment,the hole failure process could be divided into four periods:quiet,particle ejection,stability failure and collapse.Correspondingly,the AE signals evolved from a calm stage,to have intermittent appearance;then,they were continuous with a sudden increase,and finally increased dramatically.The failure of the surrounding rock was mainly tensile failure,while shear failure tended to first increase and then decrease.Meanwhile,damage to the hole increased gradually during the particle ejection period,whereas damage to the rockburst mainly occurred in the stability failure period.The thermal radiation temperature migration exhibited warming in shallow parts,inward expansion,cooling in the shallow parts with free surface heating,inward expansion,a sudden rise in temperature of the rockburst pits,and finally specimen failure.The initial reinforcement support should fully contribute to surface support.Furthermore,an appropriate tensile capacity and good energy absorption capacity should be established in support systems for high-stress roadways.展开更多
Climate sequences can be applied to defining sensitive climate zones, and then the mining of spatio-temporal teleconnection patterns is useful for learning from the past and preparing for the future. However, scale-de...Climate sequences can be applied to defining sensitive climate zones, and then the mining of spatio-temporal teleconnection patterns is useful for learning from the past and preparing for the future. However, scale-dependency in this kind of pattern is still not well handled by existing work. Therefore, in this study, the multi-scale regionalization is embedded into the spatio-temporal teleconnection pattern mining between anomalous sea and land climatic events. A modified scale-space clustering algorithm is first developed to group climate sequences into multi-scale climate zones. Then, scale variance analysis method is employed to identify climate zones at characteristic scales, indicating the main characteristics of geographical phenomena. Finally, by using the climate zones identified at characteristic scales, a time association rule mining algorithm based on sliding time windows is employed to discover spatio-temporal teleconnection patterns. Experiments on sea surface temperature, sea level pressure, land precipitation and land temperature datasets show that many patterns obtained by the multi-scale approach are coincident with prior knowledge, indicating that this method is effective and reasonable. In addition, some unknown teleconnection patterns discovered from the multi-scale approach can be further used to guide the prediction of land climate.展开更多
Owing to the wide range of applications in various fields,generative models have become increasingly popular.However,they do not handle spatio-temporal features well.Inspired by the recent advances in these models,thi...Owing to the wide range of applications in various fields,generative models have become increasingly popular.However,they do not handle spatio-temporal features well.Inspired by the recent advances in these models,this paper designs a distributed spatio-temporal generative adversarial network(STGAN-D)that,given some initial data and random noise,generates a consecutive sequence of spatio-temporal samples which have a logical relationship.This paper builds a spatio-temporal discriminator to distinguish whether the samples generated by the generator meet the requirements for time and space coherence,and builds a controller for distributed training of the network gradient updated to separate the model training and parameter updating,to improve the network training rate.The model is trained on the skeletal dataset and the traffic dataset.In contrast to traditional generative adversarial networks(GANs),the proposed STGAN-D can generate logically coherent samples with the corresponding spatial and temporal features while avoiding mode collapse.In addition,this paper shows that the proposed model can generate different styles of spatio-temporal samples given different random noise inputs,and the controller can improve the network training rate.This model will extend the potential range of applications of GANs to areas such as traffic information simulation and multiagent adversarial simulation.展开更多
Short-term travel flow prediction has been the core of the intelligent transport systems(ITS). An advanced method based on fuzzy C-means(FCM) and extreme learning machine(ELM) has been discussed by analyzing predictio...Short-term travel flow prediction has been the core of the intelligent transport systems(ITS). An advanced method based on fuzzy C-means(FCM) and extreme learning machine(ELM) has been discussed by analyzing prediction model. First, this model takes advantages of ability to adapt to nonlinear systems and the fast speed of ELM algorithm. Second, with FCM-clustering function, this novel model can get the clusters and the membership in the same cluster, which means that the associated observation points have been chosen. Therefore, the spatial relations can be used by giving the weight to every observation points when the model trains and tests the ELM. Third, by analyzing the actual data in Haining City in 2016, the feasibility and advantages of FCM-ELM prediction model have been shown when compared with other prediction algorithms.展开更多
De-interlacing is very important when converting interlaced pictures to progressive pictures in format conversion. Multi-formats digital broadcast and progressive display requires the de-interlacing technique. An adap...De-interlacing is very important when converting interlaced pictures to progressive pictures in format conversion. Multi-formats digital broadcast and progressive display requires the de-interlacing technique. An adaptive weight de interlacing method is proposed. It combines motion compensation technique with directional-based spatio-temporal filter efficiently. Experiment results indicate that the method can keep edge continuity and sharpness effectively, reduce the artifacts in motion areas, and shows better visual performance when the estimated motion vectors are inaccurate.展开更多
基金supported by Beijing Insititute of Technology Research Fund Program for Young Scholars(2020X04104)。
文摘In this paper,an improved spatio-temporal alignment measurement method is presented to address the inertial matching measurement of hull deformation under the coexistence of time delay and large misalignment angle.Large misalignment angle and time delay often occur simultaneously and bring great challenges to the accurate measurement of hull deformation in space and time.The proposed method utilizes coarse alignment with large misalignment angle and time delay estimation of inertial measurement unit modeling to establish a brand-new spatiotemporal aligned hull deformation measurement model.In addition,two-step loop control is designed to ensure the accurate description of dynamic deformation angle and static deformation angle by the time-space alignment method of hull deformation.The experiments illustrate that the proposed method can effectively measure the hull deformation angle when time delay and large misalignment angle coexist.
基金Key Basic Research Project of Strengthening the Foundations Plan of China (Grant No.2019-JCJQ-ZD-360-12)National Defense Basic Scientific Research Program of China (Grant No.JCKY2021208B011)to provide fund for conducting experiments。
文摘High speed photography technique is potentially the most effective way to measure the motion parameter of warhead fragment benefiting from its advantages of high accuracy,high resolution and high efficiency.However,it faces challenge in dense objects tracking and 3D trajectories reconstruction due to the characteristics of small size and dense distribution of fragment swarm.To address these challenges,this work presents a warhead fragments motion trajectories tracking and spatio-temporal distribution reconstruction method based on high-speed stereo photography.Firstly,background difference algorithm is utilized to extract the center and area of each fragment in the image sequence.Subsequently,a multi-object tracking(MOT)algorithm using Kalman filtering and Hungarian optimal assignment is developed to realize real-time and robust trajectories tracking of fragment swarm.To reconstruct 3D motion trajectories,a global stereo trajectories matching strategy is presented,which takes advantages of epipolar constraint and continuity constraint to correctly retrieve stereo correspondence followed by 3D trajectories refinement using polynomial fitting.Finally,the simulation and experimental results demonstrate that the proposed method can accurately track the motion trajectories and reconstruct the spatio-temporal distribution of 1.0×10^(3)fragments in a field of view(FOV)of 3.2 m×2.5 m,and the accuracy of the velocity estimation can achieve 98.6%.
基金supported by National Natural Science Foundation of China(Grant No.62073256)the Shaanxi Provincial Science and Technology Department(Grant No.2023-YBGY-342).
文摘To solve the problem of target damage assessment when fragments attack target under uncertain projectile and target intersection in an air defense intercept,this paper proposes a method for calculating target damage probability leveraging spatio-temporal finite multilayer fragments distribution and the target damage assessment algorithm based on cloud model theory.Drawing on the spatial dispersion characteristics of fragments of projectile proximity explosion,we divide into a finite number of fragments distribution planes based on the time series in space,set up a fragment layer dispersion model grounded in the time series and intersection criterion for determining the effective penetration of each layer of fragments into the target.Building on the precondition that the multilayer fragments of the time series effectively assail the target,we also establish the damage criterion of the perforation and penetration damage and deduce the damage probability calculation model.Taking the damage probability of the fragment layer in the spatio-temporal sequence to the target as the input state variable,we introduce cloud model theory to research the target damage assessment method.Combining the equivalent simulation experiment,the scientific and rational nature of the proposed method were validated through quantitative calculations and comparative analysis.
基金Project(2017YFC0603003)supported by the National Key Research and Development Project of ChinaProjects(51974009,51674008)supported by the National Natural Science Foundation of China+3 种基金Project(201904a07020010)supported by the Key Research and Development Program of Anhui Province,ChinaProject(2018D187)supported by the Leading Talent Project of Anhui“Special Support Program”,Anhui Provincial Academic and Technology Leaders Research Activities Funding,ChinaProject(gxbjZD2016051)supported by the Excellence Talent Training Program of High School,ChinaProject(2019CX2008)supported by the Graduate Innovation Fund of Anhui University of Science and Technology,China。
文摘To study the mechanism of rockburst and its spatio-temporal evolution criterion,a rockburst simulation experiment was performed on granite specimens,each with a prefabricated circular hole,under different lateral loads.Using micro camera,acoustic emission(AE)system,and infrared thermal imager,the AE characteristics and thermal radiation temperature migration were studied during the rockburst process.Then,the failure mode and damage evolution of the surrounding rock were analyzed.The results demonstrate that increasing the lateral load can first increase and then reduce the bearing capacity of the hole.In this experiment,the hole failure process could be divided into four periods:quiet,particle ejection,stability failure and collapse.Correspondingly,the AE signals evolved from a calm stage,to have intermittent appearance;then,they were continuous with a sudden increase,and finally increased dramatically.The failure of the surrounding rock was mainly tensile failure,while shear failure tended to first increase and then decrease.Meanwhile,damage to the hole increased gradually during the particle ejection period,whereas damage to the rockburst mainly occurred in the stability failure period.The thermal radiation temperature migration exhibited warming in shallow parts,inward expansion,cooling in the shallow parts with free surface heating,inward expansion,a sudden rise in temperature of the rockburst pits,and finally specimen failure.The initial reinforcement support should fully contribute to surface support.Furthermore,an appropriate tensile capacity and good energy absorption capacity should be established in support systems for high-stress roadways.
基金Projects(41601424,41171351)supported by the National Natural Science Foundation of ChinaProject(2012CB719906)supported by the National Basic Research Program of China(973 Program)+2 种基金Project(14JJ1007)supported by the Hunan Natural Science Fund for Distinguished Young Scholars,ChinaProject(2017M610486)supported by the China Postdoctoral Science FoundationProjects(2017YFB0503700,2017YFB0503601)supported by the National Key Research and Development Foundation of China
文摘Climate sequences can be applied to defining sensitive climate zones, and then the mining of spatio-temporal teleconnection patterns is useful for learning from the past and preparing for the future. However, scale-dependency in this kind of pattern is still not well handled by existing work. Therefore, in this study, the multi-scale regionalization is embedded into the spatio-temporal teleconnection pattern mining between anomalous sea and land climatic events. A modified scale-space clustering algorithm is first developed to group climate sequences into multi-scale climate zones. Then, scale variance analysis method is employed to identify climate zones at characteristic scales, indicating the main characteristics of geographical phenomena. Finally, by using the climate zones identified at characteristic scales, a time association rule mining algorithm based on sliding time windows is employed to discover spatio-temporal teleconnection patterns. Experiments on sea surface temperature, sea level pressure, land precipitation and land temperature datasets show that many patterns obtained by the multi-scale approach are coincident with prior knowledge, indicating that this method is effective and reasonable. In addition, some unknown teleconnection patterns discovered from the multi-scale approach can be further used to guide the prediction of land climate.
基金the National Natural Science Foundation of China(61573285).
文摘Owing to the wide range of applications in various fields,generative models have become increasingly popular.However,they do not handle spatio-temporal features well.Inspired by the recent advances in these models,this paper designs a distributed spatio-temporal generative adversarial network(STGAN-D)that,given some initial data and random noise,generates a consecutive sequence of spatio-temporal samples which have a logical relationship.This paper builds a spatio-temporal discriminator to distinguish whether the samples generated by the generator meet the requirements for time and space coherence,and builds a controller for distributed training of the network gradient updated to separate the model training and parameter updating,to improve the network training rate.The model is trained on the skeletal dataset and the traffic dataset.In contrast to traditional generative adversarial networks(GANs),the proposed STGAN-D can generate logically coherent samples with the corresponding spatial and temporal features while avoiding mode collapse.In addition,this paper shows that the proposed model can generate different styles of spatio-temporal samples given different random noise inputs,and the controller can improve the network training rate.This model will extend the potential range of applications of GANs to areas such as traffic information simulation and multiagent adversarial simulation.
基金Project(2016YFB0100906)supported by the National Key R&D Program in ChinaProject(2014BAG03B01)supported by the National Science and Technology Support plan Project China+1 种基金Project(61673232)supported by the National Natural Science Foundation of ChinaProjects(Dl S11090028000,D171100006417003)supported by Beijing Municipal Science and Technology Program,China
文摘Short-term travel flow prediction has been the core of the intelligent transport systems(ITS). An advanced method based on fuzzy C-means(FCM) and extreme learning machine(ELM) has been discussed by analyzing prediction model. First, this model takes advantages of ability to adapt to nonlinear systems and the fast speed of ELM algorithm. Second, with FCM-clustering function, this novel model can get the clusters and the membership in the same cluster, which means that the associated observation points have been chosen. Therefore, the spatial relations can be used by giving the weight to every observation points when the model trains and tests the ELM. Third, by analyzing the actual data in Haining City in 2016, the feasibility and advantages of FCM-ELM prediction model have been shown when compared with other prediction algorithms.
文摘De-interlacing is very important when converting interlaced pictures to progressive pictures in format conversion. Multi-formats digital broadcast and progressive display requires the de-interlacing technique. An adaptive weight de interlacing method is proposed. It combines motion compensation technique with directional-based spatio-temporal filter efficiently. Experiment results indicate that the method can keep edge continuity and sharpness effectively, reduce the artifacts in motion areas, and shows better visual performance when the estimated motion vectors are inaccurate.
