The generation and reconnection of magneticflux ropes in a plasma irradiated by two Laguerre–Gaussian laser pulses with different frequen-cies and opposite topological charges are investigated numerically by particle-...The generation and reconnection of magneticflux ropes in a plasma irradiated by two Laguerre–Gaussian laser pulses with different frequen-cies and opposite topological charges are investigated numerically by particle-in-cell simulations.It is shown that twisted plasma currents and hence magneticflux ropes can be effectively generated as long as the laser frequency difference matches the electron plasma frequency.More importantly,subsequent reconnection of magneticflux ropes can occur.Typical signatures of magnetic reconnection,such as magnetic island formation and plasma heating,are identified in the reconnection of magneticflux ropes.Notably,it is found that a strong axial magneticfield can be generated on the axis,owing to the azimuthal current induced during the reconnection of the ropes.This indicates that in the reconnection of magneticflux ropes,the energy can be transferred not only from the magneticfield to the plasma but also from the plasma current back to the magneticfield.This work opens a new avenue to the study of magneticflux ropes,which helps in understanding magnetic topology changes,and resultant magnetic energy dissipation,plasma heating,and particle acceleration found in solarflares,and magnetic confinement fusion devices.展开更多
Wire rope inspection robot is an important tool for wire rope condition monitoring and maintenance,which can accurately locate and judge the damage of wire rope.In addition,the wire rope inspection robot can also be u...Wire rope inspection robot is an important tool for wire rope condition monitoring and maintenance,which can accurately locate and judge the damage of wire rope.In addition,the wire rope inspection robot can also be used for cable inspection.First,the crawling structure and crawling mode of the wire rope inspection robot are reviewed,and the characteristics and existing problems of each crawling mode are analyzed separately.Next,the drive mode of the wire rope inspection robot is discussed,the types of commonly used motors are introduced,and the advantages and disadvantages of drive motors and the control modes are compared.Then,the method and principle of the non-destructive detection of the wire rope inspection robot are expounded,and the commonly used detection methods and existing deficiencies are compared.After that,the types of communication modes are compared and analyzed,and the types of wireless communication modes are also introduced.Finally,the current difficult problems of the wire rope inspection robot are summarized,and the future development trend of the wire rope inspection robot is prospected.展开更多
In heavy-duty long-distance transmission scenarios,steel wire ropes are widely used due to their unique advantages,and their safety is very important,which has also led to the rapid development of non-destructive test...In heavy-duty long-distance transmission scenarios,steel wire ropes are widely used due to their unique advantages,and their safety is very important,which has also led to the rapid development of non-destructive testing technology for steel wire ropes.The non-destructive testing technology for steel wire ropes is influenced by various factors such as its own structure and external working environment,and the testing process is relatively complex.Multiple testing methods and related types of sensors have also emerged.The electromagnetic detection method is currently the most effective method,but it also has its limitations in development and has not yet fully achieved the expected detection goals.In order to completely replace manual inspection work with the development of non-destructive testing technology for steel wire ropes,more in-depth research and long-term accumulation are still needed.展开更多
The complex geometrical features of mechanical components significantly influence contact interactions and system dynamics.However,directly modeling contact forces on surfaces with intricate geometries presents consid...The complex geometrical features of mechanical components significantly influence contact interactions and system dynamics.However,directly modeling contact forces on surfaces with intricate geometries presents considerable challenges.This study focuses on the helically twisted wire rope-sheave contact and proposes a contact force model that incorporates complex geometric features through a parameter identification approach.The model's impact on contact forces and system dynamics is thoroughly investigated.Leveraging a point contact model and an elliptic integral approximation,a loss function is formulated using the finite element(FE)contact model results as the reference data.Geometric parameters are subsequently determined by optimizing this loss function via a genetic algorithm(GA).The findings reveal that the contact stiffness increases with the wire rope pitch length,the radius of principal curvature,and the elliptic eccentricity of the contact zone.The proposed contact force model is integrated into a rigid-flexible coupled dynamics model,developed by the absolute node coordinate formulation,to examine the effects of contact geometry on system dynamics.The results demonstrate that the variations in wire rope geometry alter the contact stiffness,which in turn affects dynamic rope tension through frictional energy dissipation.The enhanced model's predictions exhibit superior alignment with the experimental data,thereby validating the methodology.This approach provides new insights for deducing the contact geometry from kinetic parameters and monitoring the performance degradation of mechanical components.展开更多
This study investigates cavitating swirling flow in a diffuser,i.e.,a simplified model of a Francis turbine draft tube,using proper orthogonal decomposition(POD)and dynamic mode decomposition(DMD)applied to velocity a...This study investigates cavitating swirling flow in a diffuser,i.e.,a simplified model of a Francis turbine draft tube,using proper orthogonal decomposition(POD)and dynamic mode decomposition(DMD)applied to velocity and pressure field data.The interaction between vortex rope precession and cavitation surge under varying swirl and cavitation numbers is analyzed.The modal analysis results depicted the coherent structures correlated to the vortex rope precession near the diffuser inlet and the diffuser outlet,and cavitation surge in the diffuser.The POD analysis accurately revealed the flow features in the diffuser:The conical structure represents the flow diffusion with vortex rope precession and the reverse core indicates the backflow in the diffuser for the averaged flow,and the double helical structure near the diffuser inlet for the representative flow oscillation.The typical coherent structures obtained by the DMD for the cavitating swirling flow in the diffuser are the double helical structure concentrated near the diffuser inlet.The double helical structure also appears near the diffuser outlet where the breakdown of vortex rope occurs and the flow oscillation slows down.Once cavitation occurs,the mode induced by cavitation surge and its corresponding coherent structure may change according to the operating condition.The flow oscillation can be changed from the double helical mode to the axial oscillation caused by cavitation surge named breathing mode if cavitation surge becomes strong enough at a small cavitation number or large swirl number.展开更多
Aimed at the long and narrow geometric features and poor generalization ability of the damage detection in conveyor belts with steel rope cores using the X-ray image,a detection method of damage X-ray image is propose...Aimed at the long and narrow geometric features and poor generalization ability of the damage detection in conveyor belts with steel rope cores using the X-ray image,a detection method of damage X-ray image is proposed based on the improved fully convolutional one-stage object detection(FCOS)algorithm.The regression performance of bounding boxes was optimized by introducing the complete intersection over union loss function into the improved algorithm.The feature fusion network structure is modified by adding adaptive fusion paths to the feature fusion network structure,which makes full use of the features of accurate localization and semantics of multi-scale feature fusion networks.Finally,the network structure was trained and validated by using the X-ray image dataset of damages in conveyor belts with steel rope cores provided by a flaw detection equipment manufacturer.In addition,the data enhancement methods such as rotating,mirroring,and scaling,were employed to enrich the image dataset so that the model is adequately trained.Experimental results showed that the improved FCOS algorithm promoted the precision rate and the recall rate by 20.9%and 14.8%respectively,compared with the original algorithm.Meanwhile,compared with Fast R-CNN,Faster R-CNN,SSD,and YOLOv3,the improved FCOS algorithm has obvious advantages;detection precision rate and recall rate of the modified network reached 95.8%and 97.0%respectively.Furthermore,it demonstrated a higher detection accuracy without affecting the speed.The results of this work have some reference significance for the automatic identification and detection of steel core conveyor belt damage.展开更多
针对水电机组状态监测数据量逐步增大,数据质量差的问题,提出了一种基于改进K维树(K-Dimensional Tree,KD-Tree)与基于密度的空间聚类算法(Density-Based Spatial Clustering of Applications with Noise,DBSCAN)的水电机组状态监测数...针对水电机组状态监测数据量逐步增大,数据质量差的问题,提出了一种基于改进K维树(K-Dimensional Tree,KD-Tree)与基于密度的空间聚类算法(Density-Based Spatial Clustering of Applications with Noise,DBSCAN)的水电机组状态监测数据清洗方法,首先对输入数据建立KD-Tree,再使用DBSCAN在最近邻样本上扫描完成聚类,聚类结束以后会分离出噪声点,将噪声点去除即可完成对水电机组状态监测数据清洗。选取某水电站状态监测系统上导摆度数据1 088条,再以相同时间间隔插入随机数据100条,通过算例与常规DBScan、K-means、OCSVM算法对比聚类性能与时间性能,所提出的方法识别正确率最高,为97.78%,消耗时间最少,为0.007 732 s,数据清洗效果最优,并可以大幅减少计算时间。展开更多
Traditional clustering algorithms often struggle to produce satisfactory results when dealing with datasets withuneven density. Additionally, they incur substantial computational costs when applied to high-dimensional...Traditional clustering algorithms often struggle to produce satisfactory results when dealing with datasets withuneven density. Additionally, they incur substantial computational costs when applied to high-dimensional datadue to calculating similarity matrices. To alleviate these issues, we employ the KD-Tree to partition the dataset andcompute the K-nearest neighbors (KNN) density for each point, thereby avoiding the computation of similaritymatrices. Moreover, we apply the rules of voting elections, treating each data point as a voter and casting a votefor the point with the highest density among its KNN. By utilizing the vote counts of each point, we develop thestrategy for classifying noise points and potential cluster centers, allowing the algorithm to identify clusters withuneven density and complex shapes. Additionally, we define the concept of “adhesive points” between two clustersto merge adjacent clusters that have similar densities. This process helps us identify the optimal number of clustersautomatically. Experimental results indicate that our algorithm not only improves the efficiency of clustering butalso increases its accuracy.展开更多
Data stream clustering is integral to contemporary big data applications.However,addressing the ongoing influx of data streams efficiently and accurately remains a primary challenge in current research.This paper aims...Data stream clustering is integral to contemporary big data applications.However,addressing the ongoing influx of data streams efficiently and accurately remains a primary challenge in current research.This paper aims to elevate the efficiency and precision of data stream clustering,leveraging the TEDA(Typicality and Eccentricity Data Analysis)algorithm as a foundation,we introduce improvements by integrating a nearest neighbor search algorithm to enhance both the efficiency and accuracy of the algorithm.The original TEDA algorithm,grounded in the concept of“Typicality and Eccentricity Data Analytics”,represents an evolving and recursive method that requires no prior knowledge.While the algorithm autonomously creates and merges clusters as new data arrives,its efficiency is significantly hindered by the need to traverse all existing clusters upon the arrival of further data.This work presents the NS-TEDA(Neighbor Search Based Typicality and Eccentricity Data Analysis)algorithm by incorporating a KD-Tree(K-Dimensional Tree)algorithm integrated with the Scapegoat Tree.Upon arrival,this ensures that new data points interact solely with clusters in very close proximity.This significantly enhances algorithm efficiency while preventing a single data point from joining too many clusters and mitigating the merging of clusters with high overlap to some extent.We apply the NS-TEDA algorithm to several well-known datasets,comparing its performance with other data stream clustering algorithms and the original TEDA algorithm.The results demonstrate that the proposed algorithm achieves higher accuracy,and its runtime exhibits almost linear dependence on the volume of data,making it more suitable for large-scale data stream analysis research.展开更多
The multi-robot coordinated lifting system is an unconstrained system with a rigid and flexible coupling.The deformation of the flexible rope causes errors in the movement trajectory of the lifting system.Based on the...The multi-robot coordinated lifting system is an unconstrained system with a rigid and flexible coupling.The deformation of the flexible rope causes errors in the movement trajectory of the lifting system.Based on the kinematic and dynamic analysis of the lifting system,the elastic catenary mod-el considering the elasticity and mass of the flexible rope is established,and the effect of the deform-ation of the flexible rope on the position and posture of the suspended object is analyzed.According to the deformation of flexible rope,a real-time trajectory compensation method is proposed based on the compensation principle of position and posture.Under the lifting task of the low-speed move-ment,this is compared with that of the system which neglects the deformation of the flexible rope.The trajectoy of the lifting system considering the deformation of flexible rope.The results show that the mass and elasticity of the flexible rope can not be neglected.Meanwhile,the proposed trajectory compensation method can improve the movement accuracy of the lifting system,which verifies the ef-fectiveness of this compensation method.The research results provide the basis for trajectory plan-ning and coordinated control of the lifting system。展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.12375236 and 12135009)the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant Nos.XDA25050100 and XDA25010100).
文摘The generation and reconnection of magneticflux ropes in a plasma irradiated by two Laguerre–Gaussian laser pulses with different frequen-cies and opposite topological charges are investigated numerically by particle-in-cell simulations.It is shown that twisted plasma currents and hence magneticflux ropes can be effectively generated as long as the laser frequency difference matches the electron plasma frequency.More importantly,subsequent reconnection of magneticflux ropes can occur.Typical signatures of magnetic reconnection,such as magnetic island formation and plasma heating,are identified in the reconnection of magneticflux ropes.Notably,it is found that a strong axial magneticfield can be generated on the axis,owing to the azimuthal current induced during the reconnection of the ropes.This indicates that in the reconnection of magneticflux ropes,the energy can be transferred not only from the magneticfield to the plasma but also from the plasma current back to the magneticfield.This work opens a new avenue to the study of magneticflux ropes,which helps in understanding magnetic topology changes,and resultant magnetic energy dissipation,plasma heating,and particle acceleration found in solarflares,and magnetic confinement fusion devices.
基金the National Natural Science Foundation of China(No.12072362)the Priority Academic Program Development of Jiangsu Higher Education Institutions。
文摘Wire rope inspection robot is an important tool for wire rope condition monitoring and maintenance,which can accurately locate and judge the damage of wire rope.In addition,the wire rope inspection robot can also be used for cable inspection.First,the crawling structure and crawling mode of the wire rope inspection robot are reviewed,and the characteristics and existing problems of each crawling mode are analyzed separately.Next,the drive mode of the wire rope inspection robot is discussed,the types of commonly used motors are introduced,and the advantages and disadvantages of drive motors and the control modes are compared.Then,the method and principle of the non-destructive detection of the wire rope inspection robot are expounded,and the commonly used detection methods and existing deficiencies are compared.After that,the types of communication modes are compared and analyzed,and the types of wireless communication modes are also introduced.Finally,the current difficult problems of the wire rope inspection robot are summarized,and the future development trend of the wire rope inspection robot is prospected.
文摘In heavy-duty long-distance transmission scenarios,steel wire ropes are widely used due to their unique advantages,and their safety is very important,which has also led to the rapid development of non-destructive testing technology for steel wire ropes.The non-destructive testing technology for steel wire ropes is influenced by various factors such as its own structure and external working environment,and the testing process is relatively complex.Multiple testing methods and related types of sensors have also emerged.The electromagnetic detection method is currently the most effective method,but it also has its limitations in development and has not yet fully achieved the expected detection goals.In order to completely replace manual inspection work with the development of non-destructive testing technology for steel wire ropes,more in-depth research and long-term accumulation are still needed.
基金supported by the National Key Research and Development Program of China(No.2023YFC3010400)。
文摘The complex geometrical features of mechanical components significantly influence contact interactions and system dynamics.However,directly modeling contact forces on surfaces with intricate geometries presents considerable challenges.This study focuses on the helically twisted wire rope-sheave contact and proposes a contact force model that incorporates complex geometric features through a parameter identification approach.The model's impact on contact forces and system dynamics is thoroughly investigated.Leveraging a point contact model and an elliptic integral approximation,a loss function is formulated using the finite element(FE)contact model results as the reference data.Geometric parameters are subsequently determined by optimizing this loss function via a genetic algorithm(GA).The findings reveal that the contact stiffness increases with the wire rope pitch length,the radius of principal curvature,and the elliptic eccentricity of the contact zone.The proposed contact force model is integrated into a rigid-flexible coupled dynamics model,developed by the absolute node coordinate formulation,to examine the effects of contact geometry on system dynamics.The results demonstrate that the variations in wire rope geometry alter the contact stiffness,which in turn affects dynamic rope tension through frictional energy dissipation.The enhanced model's predictions exhibit superior alignment with the experimental data,thereby validating the methodology.This approach provides new insights for deducing the contact geometry from kinetic parameters and monitoring the performance degradation of mechanical components.
基金Project supported by the National Natural Science Foundation of China(Grant No.52336001)supported by the Tsinghua National Laboratory for Information Science and Technology.
文摘This study investigates cavitating swirling flow in a diffuser,i.e.,a simplified model of a Francis turbine draft tube,using proper orthogonal decomposition(POD)and dynamic mode decomposition(DMD)applied to velocity and pressure field data.The interaction between vortex rope precession and cavitation surge under varying swirl and cavitation numbers is analyzed.The modal analysis results depicted the coherent structures correlated to the vortex rope precession near the diffuser inlet and the diffuser outlet,and cavitation surge in the diffuser.The POD analysis accurately revealed the flow features in the diffuser:The conical structure represents the flow diffusion with vortex rope precession and the reverse core indicates the backflow in the diffuser for the averaged flow,and the double helical structure near the diffuser inlet for the representative flow oscillation.The typical coherent structures obtained by the DMD for the cavitating swirling flow in the diffuser are the double helical structure concentrated near the diffuser inlet.The double helical structure also appears near the diffuser outlet where the breakdown of vortex rope occurs and the flow oscillation slows down.Once cavitation occurs,the mode induced by cavitation surge and its corresponding coherent structure may change according to the operating condition.The flow oscillation can be changed from the double helical mode to the axial oscillation caused by cavitation surge named breathing mode if cavitation surge becomes strong enough at a small cavitation number or large swirl number.
文摘Aimed at the long and narrow geometric features and poor generalization ability of the damage detection in conveyor belts with steel rope cores using the X-ray image,a detection method of damage X-ray image is proposed based on the improved fully convolutional one-stage object detection(FCOS)algorithm.The regression performance of bounding boxes was optimized by introducing the complete intersection over union loss function into the improved algorithm.The feature fusion network structure is modified by adding adaptive fusion paths to the feature fusion network structure,which makes full use of the features of accurate localization and semantics of multi-scale feature fusion networks.Finally,the network structure was trained and validated by using the X-ray image dataset of damages in conveyor belts with steel rope cores provided by a flaw detection equipment manufacturer.In addition,the data enhancement methods such as rotating,mirroring,and scaling,were employed to enrich the image dataset so that the model is adequately trained.Experimental results showed that the improved FCOS algorithm promoted the precision rate and the recall rate by 20.9%and 14.8%respectively,compared with the original algorithm.Meanwhile,compared with Fast R-CNN,Faster R-CNN,SSD,and YOLOv3,the improved FCOS algorithm has obvious advantages;detection precision rate and recall rate of the modified network reached 95.8%and 97.0%respectively.Furthermore,it demonstrated a higher detection accuracy without affecting the speed.The results of this work have some reference significance for the automatic identification and detection of steel core conveyor belt damage.
基金National Natural Science Foundation of China Nos.61962054 and 62372353.
文摘Traditional clustering algorithms often struggle to produce satisfactory results when dealing with datasets withuneven density. Additionally, they incur substantial computational costs when applied to high-dimensional datadue to calculating similarity matrices. To alleviate these issues, we employ the KD-Tree to partition the dataset andcompute the K-nearest neighbors (KNN) density for each point, thereby avoiding the computation of similaritymatrices. Moreover, we apply the rules of voting elections, treating each data point as a voter and casting a votefor the point with the highest density among its KNN. By utilizing the vote counts of each point, we develop thestrategy for classifying noise points and potential cluster centers, allowing the algorithm to identify clusters withuneven density and complex shapes. Additionally, we define the concept of “adhesive points” between two clustersto merge adjacent clusters that have similar densities. This process helps us identify the optimal number of clustersautomatically. Experimental results indicate that our algorithm not only improves the efficiency of clustering butalso increases its accuracy.
基金This research was funded by the National Natural Science Foundation of China(Grant No.72001190)by the Ministry of Education’s Humanities and Social Science Project via the China Ministry of Education(Grant No.20YJC630173)by Zhejiang A&F University(Grant No.2022LFR062).
文摘Data stream clustering is integral to contemporary big data applications.However,addressing the ongoing influx of data streams efficiently and accurately remains a primary challenge in current research.This paper aims to elevate the efficiency and precision of data stream clustering,leveraging the TEDA(Typicality and Eccentricity Data Analysis)algorithm as a foundation,we introduce improvements by integrating a nearest neighbor search algorithm to enhance both the efficiency and accuracy of the algorithm.The original TEDA algorithm,grounded in the concept of“Typicality and Eccentricity Data Analytics”,represents an evolving and recursive method that requires no prior knowledge.While the algorithm autonomously creates and merges clusters as new data arrives,its efficiency is significantly hindered by the need to traverse all existing clusters upon the arrival of further data.This work presents the NS-TEDA(Neighbor Search Based Typicality and Eccentricity Data Analysis)algorithm by incorporating a KD-Tree(K-Dimensional Tree)algorithm integrated with the Scapegoat Tree.Upon arrival,this ensures that new data points interact solely with clusters in very close proximity.This significantly enhances algorithm efficiency while preventing a single data point from joining too many clusters and mitigating the merging of clusters with high overlap to some extent.We apply the NS-TEDA algorithm to several well-known datasets,comparing its performance with other data stream clustering algorithms and the original TEDA algorithm.The results demonstrate that the proposed algorithm achieves higher accuracy,and its runtime exhibits almost linear dependence on the volume of data,making it more suitable for large-scale data stream analysis research.
基金the National Natural Science Foundation of China(No.51965032)the Natural Science Foundation of Gansu Province of China(No.22JR5RA319)+1 种基金the Science and Technology Foundation of Gansu Province of China(No.21YF5WA060)the Excellent Doctoral Student Foundation of Gansu Province of China(No.23JRRA842).
文摘The multi-robot coordinated lifting system is an unconstrained system with a rigid and flexible coupling.The deformation of the flexible rope causes errors in the movement trajectory of the lifting system.Based on the kinematic and dynamic analysis of the lifting system,the elastic catenary mod-el considering the elasticity and mass of the flexible rope is established,and the effect of the deform-ation of the flexible rope on the position and posture of the suspended object is analyzed.According to the deformation of flexible rope,a real-time trajectory compensation method is proposed based on the compensation principle of position and posture.Under the lifting task of the low-speed move-ment,this is compared with that of the system which neglects the deformation of the flexible rope.The trajectoy of the lifting system considering the deformation of flexible rope.The results show that the mass and elasticity of the flexible rope can not be neglected.Meanwhile,the proposed trajectory compensation method can improve the movement accuracy of the lifting system,which verifies the ef-fectiveness of this compensation method.The research results provide the basis for trajectory plan-ning and coordinated control of the lifting system。
