Embodied visual exploration is critical for building intelligent visual agents. This paper presents the neural exploration with feature-based visual odometry and tracking-failure-reduction policy(Ne OR), a framework f...Embodied visual exploration is critical for building intelligent visual agents. This paper presents the neural exploration with feature-based visual odometry and tracking-failure-reduction policy(Ne OR), a framework for embodied visual exploration that possesses the efficient exploration capabilities of deep reinforcement learning(DRL)-based exploration policies and leverages feature-based visual odometry(VO) for more accurate mapping and positioning results. An improved local policy is also proposed to reduce tracking failures of feature-based VO in weakly textured scenes through a refined multi-discrete action space, keyframe fusion, and an auxiliary task. The experimental results demonstrate that Ne OR has better mapping and positioning accuracy compared to other entirely learning-based exploration frameworks and improves the robustness of feature-based VO by significantly reducing tracking failures in weakly textured scenes.展开更多
This paper proposes an implicit function based open-loop analysis method to detect the subsynchronous resonance(SSR),including asymmetric subsynchronous modal attraction(ASSMA)and asymmetric subsynchronous modal repul...This paper proposes an implicit function based open-loop analysis method to detect the subsynchronous resonance(SSR),including asymmetric subsynchronous modal attraction(ASSMA)and asymmetric subsynchronous modal repulsion(ASSMR),of doubly-fed induction generator based wind farms(DFIG-WFs)penetrated power systems.As some important parameters of DFIG-WF are difficult to obtain,reinforcement learning and least squares method are applied to identify those important parameters.By predicting the location of closed-loop subsynchronous oscillation(SSO)modes based on the calculation of partial differentials of characteristic equation,both ASSMA and ASSMR can be found.The proposed method in this paper can select SSO modes which move to the right half complex planes as control parameters change.Besides,the proposed open-loop analysis method is adaptive to parameter uncertainty.Simulation studies are carried out on the 4-machine 11-bus power system to verify properties of the proposed method.展开更多
Constructing vertical shafts in densely populated urban areas with complex geological conditions poses significant challenges,necessitating innovative construction techniques and design optimization.This study investi...Constructing vertical shafts in densely populated urban areas with complex geological conditions poses significant challenges,necessitating innovative construction techniques and design optimization.This study investigates the deformation behavior of a 42.5 m deep shaft excavated using the vertical shaft sinking machine(VSM)method in Shanghai’s soft soil conditions comprising deep cohesive soil layers.Comprehensive numerical analysis simulated the VSM construction process,analysing deformations within the shaft structure,surrounding soil,and adjacent buildings while evaluating the influence of varying reinforced ring base depths.Results reveal a significant 30%reduction in the maximum lateral shaft deformation,from 28 to 20 mm,by increasing the reinforced ring base depth to an optimal 16 m,enhancing lateral stability.Vertical deformations exhibited complex settlement and uplift mechanisms in segmental rings and piles,influenced by factors like excavation stages,pile installation,water pressures,and adjacent loads.The optimal 16 m depth effectively mitigated uplift,and optimized load distribution,limiting the maximum settlement to 12 mm while minimizing dewatering-induced uplift effects.Analysis indicated reduced lateral movements and settlements in surrounding buildings with increasing distance from excavation,highlighting VSM’s potential for minimizing impacts on neighboring structures.This study emphasizes VSM’s suitability for shaft projects in geologically complex areas,providing insights for design,mitigating environmental impacts,and enhancing deep excavation safety and efficiency in soft soils.The findings contribute to optimizing vertical shaft construction,ensuring successful underground infrastructure execution in challenging conditions.Identifying the optimal reinforced ring base depth promotes sustainable urban development by minimizing disturbances.This research advances innovative methods and strategies for complex underground projects.展开更多
基金supported by the National Natural Science Foundation of China (No.62202137)the China Postdoctoral Science Foundation (No.2023M730599)the Zhejiang Provincial Natural Science Foundation of China (No.LMS25F020009)。
文摘Embodied visual exploration is critical for building intelligent visual agents. This paper presents the neural exploration with feature-based visual odometry and tracking-failure-reduction policy(Ne OR), a framework for embodied visual exploration that possesses the efficient exploration capabilities of deep reinforcement learning(DRL)-based exploration policies and leverages feature-based visual odometry(VO) for more accurate mapping and positioning results. An improved local policy is also proposed to reduce tracking failures of feature-based VO in weakly textured scenes through a refined multi-discrete action space, keyframe fusion, and an auxiliary task. The experimental results demonstrate that Ne OR has better mapping and positioning accuracy compared to other entirely learning-based exploration frameworks and improves the robustness of feature-based VO by significantly reducing tracking failures in weakly textured scenes.
基金supported in part by the State Key Program of National Natural Science Foundation of China under Grant No.U1866210the National Natural Science Foundation of China under Grant No.51807067.
文摘This paper proposes an implicit function based open-loop analysis method to detect the subsynchronous resonance(SSR),including asymmetric subsynchronous modal attraction(ASSMA)and asymmetric subsynchronous modal repulsion(ASSMR),of doubly-fed induction generator based wind farms(DFIG-WFs)penetrated power systems.As some important parameters of DFIG-WF are difficult to obtain,reinforcement learning and least squares method are applied to identify those important parameters.By predicting the location of closed-loop subsynchronous oscillation(SSO)modes based on the calculation of partial differentials of characteristic equation,both ASSMA and ASSMR can be found.The proposed method in this paper can select SSO modes which move to the right half complex planes as control parameters change.Besides,the proposed open-loop analysis method is adaptive to parameter uncertainty.Simulation studies are carried out on the 4-machine 11-bus power system to verify properties of the proposed method.
基金the generous funding provided by the National Natural Science Foundation of China(Grant Nos.52078128,52178317,and 52378328).This research was conducted by utilizing their support.
文摘Constructing vertical shafts in densely populated urban areas with complex geological conditions poses significant challenges,necessitating innovative construction techniques and design optimization.This study investigates the deformation behavior of a 42.5 m deep shaft excavated using the vertical shaft sinking machine(VSM)method in Shanghai’s soft soil conditions comprising deep cohesive soil layers.Comprehensive numerical analysis simulated the VSM construction process,analysing deformations within the shaft structure,surrounding soil,and adjacent buildings while evaluating the influence of varying reinforced ring base depths.Results reveal a significant 30%reduction in the maximum lateral shaft deformation,from 28 to 20 mm,by increasing the reinforced ring base depth to an optimal 16 m,enhancing lateral stability.Vertical deformations exhibited complex settlement and uplift mechanisms in segmental rings and piles,influenced by factors like excavation stages,pile installation,water pressures,and adjacent loads.The optimal 16 m depth effectively mitigated uplift,and optimized load distribution,limiting the maximum settlement to 12 mm while minimizing dewatering-induced uplift effects.Analysis indicated reduced lateral movements and settlements in surrounding buildings with increasing distance from excavation,highlighting VSM’s potential for minimizing impacts on neighboring structures.This study emphasizes VSM’s suitability for shaft projects in geologically complex areas,providing insights for design,mitigating environmental impacts,and enhancing deep excavation safety and efficiency in soft soils.The findings contribute to optimizing vertical shaft construction,ensuring successful underground infrastructure execution in challenging conditions.Identifying the optimal reinforced ring base depth promotes sustainable urban development by minimizing disturbances.This research advances innovative methods and strategies for complex underground projects.
