Active surface technique is one of the key technologies to ensure the reflector accuracy of the millimeter/submillimeter wave large reflector antenna.The antenna is complex,large-scale,and high-precision equipment,and...Active surface technique is one of the key technologies to ensure the reflector accuracy of the millimeter/submillimeter wave large reflector antenna.The antenna is complex,large-scale,and high-precision equipment,and its active surfaces are affected by various factors that are difficult to comprehensively deal with.In this paper,based on the advantage of the deep learning method that can be improved through data learning,we propose the active adjustment value analysis method of large reflector antenna based on deep learning.This method constructs a neural network model for antenna active adjustment analysis in view of the fact that a large reflector antenna consists of multiple panels spliced together.Based on the constraint that a single actuator has to support multiple panels(usually 4),an autonomously learned neural network emphasis layer module is designed to enhance the adaptability of the active adjustment neural network model.The classical 8-meter antenna is used as a case study,the actuators have a mean adjustment error of 0.00252 mm,and the corresponding antenna surface error is0.00523 mm.This active adjustment result shows the effectiveness of the method in this paper.展开更多
Video-based action recognition is becoming a vital tool in clinical research and neuroscientific study for disorder detection and prediction.However,action recognition currently used in non-human primate(NHP)research ...Video-based action recognition is becoming a vital tool in clinical research and neuroscientific study for disorder detection and prediction.However,action recognition currently used in non-human primate(NHP)research relies heavily on intense manual labor and lacks standardized assessment.In this work,we established two standard benchmark datasets of NHPs in the laboratory:Monkeyin Lab(Mi L),which includes 13 categories of actions and postures,and MiL2D,which includes sequences of two-dimensional(2D)skeleton features.Furthermore,based on recent methodological advances in deep learning and skeleton visualization,we introduced the Monkey Monitor Kit(Mon Kit)toolbox for automatic action recognition,posture estimation,and identification of fine motor activity in monkeys.Using the datasets and Mon Kit,we evaluated the daily behaviors of wild-type cynomolgus monkeys within their home cages and experimental environments and compared these observations with the behaviors exhibited by cynomolgus monkeys possessing mutations in the MECP2 gene as a disease model of Rett syndrome(RTT).Mon Kit was used to assess motor function,stereotyped behaviors,and depressive phenotypes,with the outcomes compared with human manual detection.Mon Kit established consistent criteria for identifying behavior in NHPs with high accuracy and efficiency,thus providing a novel and comprehensive tool for assessing phenotypic behavior in monkeys.展开更多
The main surface of a large reflector antenna is composed of thousands of panels,which are inevitably deformed under natural load,leading to a great deterioration of electrical performance of the antenna.The active su...The main surface of a large reflector antenna is composed of thousands of panels,which are inevitably deformed under natural load,leading to a great deterioration of electrical performance of the antenna.The active surface technique is an effective method to compensate antenna deformation error and has been widely used.The actuator is a complex component,it has not been established in the antenna structure analysis model,which limits the theoretical analysis ability of the active surface technology.To solve this problem,an integrated structure analysis method of active surface antenna by using the simplified actuator is proposed.First,according to the supporting characteristics and adjusting function of the actuator,the complex actuator is simplified a simple structure of support beams,support truss and adjustment beam.Second,the finite element model of the active surface antenna including the simplified actuator is established.Then,the relationship between the adjustment value(load)of adjustment beam and the deformation of the antenna structure is deduced,and the integrated analysis method for realizing the active adjustment of panels is established.Finally,the model and adjustment analysis method of the active surface antenna in this paper is applied to an 8 m antenna,and satisfactory structural analysis results are obtained,which shows the effectiveness and universality of the method,and provides a reference for the modeling and adjustment analysis of the active surface antenna.展开更多
基金supported by the National Key R&D Program of China No.2021YFC220350the National Natural Science Foundation of China Nos.12303094&52165053+2 种基金the Natural Science Foundation of Xinjiang Uygur Autonomous Region Nos.2022D01C683the China Postdoctoral Science Foundation Nos.2023T160549&2021M702751in part by Guangdong Basic and Applied Basic Research Foundation Nos.2020A1515111043&2023A1515010703。
文摘Active surface technique is one of the key technologies to ensure the reflector accuracy of the millimeter/submillimeter wave large reflector antenna.The antenna is complex,large-scale,and high-precision equipment,and its active surfaces are affected by various factors that are difficult to comprehensively deal with.In this paper,based on the advantage of the deep learning method that can be improved through data learning,we propose the active adjustment value analysis method of large reflector antenna based on deep learning.This method constructs a neural network model for antenna active adjustment analysis in view of the fact that a large reflector antenna consists of multiple panels spliced together.Based on the constraint that a single actuator has to support multiple panels(usually 4),an autonomously learned neural network emphasis layer module is designed to enhance the adaptability of the active adjustment neural network model.The classical 8-meter antenna is used as a case study,the actuators have a mean adjustment error of 0.00252 mm,and the corresponding antenna surface error is0.00523 mm.This active adjustment result shows the effectiveness of the method in this paper.
基金supported by the National Key R&D Program of China (2021ZD0202805,2019YFA0709504,2021ZD0200900)National Defense Science and Technology Innovation Special Zone Spark Project (20-163-00-TS-009-152-01)+4 种基金National Natural Science Foundation of China (31900719,U20A20227,82125008)Innovative Research Team of High-level Local Universities in Shanghai,Science and Technology Committee Rising-Star Program (19QA1401400)111 Project (B18015)Shanghai Municipal Science and Technology Major Project (2018SHZDZX01)Shanghai Center for Brain Science and Brain-Inspired Technology。
文摘Video-based action recognition is becoming a vital tool in clinical research and neuroscientific study for disorder detection and prediction.However,action recognition currently used in non-human primate(NHP)research relies heavily on intense manual labor and lacks standardized assessment.In this work,we established two standard benchmark datasets of NHPs in the laboratory:Monkeyin Lab(Mi L),which includes 13 categories of actions and postures,and MiL2D,which includes sequences of two-dimensional(2D)skeleton features.Furthermore,based on recent methodological advances in deep learning and skeleton visualization,we introduced the Monkey Monitor Kit(Mon Kit)toolbox for automatic action recognition,posture estimation,and identification of fine motor activity in monkeys.Using the datasets and Mon Kit,we evaluated the daily behaviors of wild-type cynomolgus monkeys within their home cages and experimental environments and compared these observations with the behaviors exhibited by cynomolgus monkeys possessing mutations in the MECP2 gene as a disease model of Rett syndrome(RTT).Mon Kit was used to assess motor function,stereotyped behaviors,and depressive phenotypes,with the outcomes compared with human manual detection.Mon Kit established consistent criteria for identifying behavior in NHPs with high accuracy and efficiency,thus providing a novel and comprehensive tool for assessing phenotypic behavior in monkeys.
基金supported by the National Key Research and Development Program of China(Nos.2021YFC2203501 and 2021YFC2203601)the National Natural Science Foundation of China(No.52165053)+2 种基金the China Postdoctoral Science Foundation(2021M702751)the Tianshan Young Talent Project of Xinjiang(2020Q068)the Doctor Scientific Research Project of Xinjiang。
文摘The main surface of a large reflector antenna is composed of thousands of panels,which are inevitably deformed under natural load,leading to a great deterioration of electrical performance of the antenna.The active surface technique is an effective method to compensate antenna deformation error and has been widely used.The actuator is a complex component,it has not been established in the antenna structure analysis model,which limits the theoretical analysis ability of the active surface technology.To solve this problem,an integrated structure analysis method of active surface antenna by using the simplified actuator is proposed.First,according to the supporting characteristics and adjusting function of the actuator,the complex actuator is simplified a simple structure of support beams,support truss and adjustment beam.Second,the finite element model of the active surface antenna including the simplified actuator is established.Then,the relationship between the adjustment value(load)of adjustment beam and the deformation of the antenna structure is deduced,and the integrated analysis method for realizing the active adjustment of panels is established.Finally,the model and adjustment analysis method of the active surface antenna in this paper is applied to an 8 m antenna,and satisfactory structural analysis results are obtained,which shows the effectiveness and universality of the method,and provides a reference for the modeling and adjustment analysis of the active surface antenna.
