Most downloaded articles
2016, 48(4):20-25.
DOI: 10.11918/j.issn.0367-6234.2016.04.003
Abstract:
A fault tolerant control scheme based on integral sliding mode surface is developed for spacecraft attitude stabilization in the presence of actuator faults, misalignments, magnitude saturation and external disturbances simultaneously. This approach is based on a novel integral-type sliding mode control strategy to compensate for these un-desired issues without controller reconfiguration. Especially, it guarantees the reachability of the system states by involving adaptive control technique to relax the boundary information in advance. A sufficient condition for the controller to accommodate magnitude saturation is also presented and then the fault tolerant attitude control system can be guaranteed theoretically to be asymptotically stable by using Lyapunov method. Numerical simulation results shows that the proposed control law can quarantee the stability of the spacecraft attitude control system in the presence of actuators' failures, and it has good robust performance.
A fault tolerant control scheme based on integral sliding mode surface is developed for spacecraft attitude stabilization in the presence of actuator faults, misalignments, magnitude saturation and external disturbances simultaneously. This approach is based on a novel integral-type sliding mode control strategy to compensate for these un-desired issues without controller reconfiguration. Especially, it guarantees the reachability of the system states by involving adaptive control technique to relax the boundary information in advance. A sufficient condition for the controller to accommodate magnitude saturation is also presented and then the fault tolerant attitude control system can be guaranteed theoretically to be asymptotically stable by using Lyapunov method. Numerical simulation results shows that the proposed control law can quarantee the stability of the spacecraft attitude control system in the presence of actuators' failures, and it has good robust performance.
2023, 55(5):139-150.
DOI: 10.11918/202112016
Abstract:
To investigate the ground motion intensity measures suitable for evaluating high-rise structures under near-fault ground motions with pulse-like effect, this paper proposes a new ground motion intensity measure considering period elongation effect and higher mode effect based on acceleration spectrum. Taking two high-rise reinforced chimney structures (120 m and 240 m) as research objects, the correlation between damage indices (ParkAng damage index, maximum inter-story drift ratio, maximum structural curvature, maximum floor acceleration, and maximum roof displacement) of high-rise structures and 37 ground motion intensity measures was studied under near-fault ground motions using OpenSEES. Results show that the proposed intensity measure was the optimal index in predicting the ParkAng damage of high-rise concrete structures under near-fault ground motions. High correlation between velocity-related intensity measures and structural damage index was observed. As the structural period increased, the correlation between damage indices and displacement-related intensity measures was improved. Besides, peak ground acceleration had limitations in characterizing the deformation and failure of high-rise structures, but it could be used to analyze the seismic performance of non-structural components. The research results can provide reference for selecting proper measures and structural damage indices to evaluate the seismic performance of high-rise structures under near-fault ground motions.
To investigate the ground motion intensity measures suitable for evaluating high-rise structures under near-fault ground motions with pulse-like effect, this paper proposes a new ground motion intensity measure considering period elongation effect and higher mode effect based on acceleration spectrum. Taking two high-rise reinforced chimney structures (120 m and 240 m) as research objects, the correlation between damage indices (ParkAng damage index, maximum inter-story drift ratio, maximum structural curvature, maximum floor acceleration, and maximum roof displacement) of high-rise structures and 37 ground motion intensity measures was studied under near-fault ground motions using OpenSEES. Results show that the proposed intensity measure was the optimal index in predicting the ParkAng damage of high-rise concrete structures under near-fault ground motions. High correlation between velocity-related intensity measures and structural damage index was observed. As the structural period increased, the correlation between damage indices and displacement-related intensity measures was improved. Besides, peak ground acceleration had limitations in characterizing the deformation and failure of high-rise structures, but it could be used to analyze the seismic performance of non-structural components. The research results can provide reference for selecting proper measures and structural damage indices to evaluate the seismic performance of high-rise structures under near-fault ground motions.
2017, 49(3):1-14.
DOI: 10.11918/j.issn.0367-6234.2017.03.001
Abstract:
It is well known that unmanned aerial vehicle (UAV) is more and more widely applied in military and civil areas. In order to play the better role of UAV, it is needed to utilize multi UAVs cooperative formation to accomplish cooperative reconnaissance, combat, defense and spraying pesticides and other tasks. The multi UAVs cooperative formation control technology mainly contains the following key techniques: data fusion technology, sensing technology, task allocation technology, path planning technology, formation control technology, communication network technology and virtual/physical verification platform technology. Firstly, summarize the research and development of key technologies worldwide. Then, the classification for multi UAVs formation control methods is mainly investigated, and the problems about formation design and adjustment, formation reconfiguration are summarized. Finally, the challenges and future development for multi UAV cooperative formation are prospected. Research shows: at present, the theory of multi UAV formation flight has acquired fruitful results, while the real cooperative formation flight test can only be implemented in the simple communication environment. The real time performance for task allocation and path planning is not high. The robustness of control methods to cope with the unexpected situation is low. The cooperative sensing ability for multi UAV with multi sensor is insufficient. The simulation of the entity is lacked. Breaking through the above key technologies, carrying out the cooperative formation flight of multi UAV in complex sensing constraints and complex communication environment, putting forward more effective control method and carrying out the UAV physical formation flying test so that the UAV can finish the task better may be the future research directions.
It is well known that unmanned aerial vehicle (UAV) is more and more widely applied in military and civil areas. In order to play the better role of UAV, it is needed to utilize multi UAVs cooperative formation to accomplish cooperative reconnaissance, combat, defense and spraying pesticides and other tasks. The multi UAVs cooperative formation control technology mainly contains the following key techniques: data fusion technology, sensing technology, task allocation technology, path planning technology, formation control technology, communication network technology and virtual/physical verification platform technology. Firstly, summarize the research and development of key technologies worldwide. Then, the classification for multi UAVs formation control methods is mainly investigated, and the problems about formation design and adjustment, formation reconfiguration are summarized. Finally, the challenges and future development for multi UAV cooperative formation are prospected. Research shows: at present, the theory of multi UAV formation flight has acquired fruitful results, while the real cooperative formation flight test can only be implemented in the simple communication environment. The real time performance for task allocation and path planning is not high. The robustness of control methods to cope with the unexpected situation is low. The cooperative sensing ability for multi UAV with multi sensor is insufficient. The simulation of the entity is lacked. Breaking through the above key technologies, carrying out the cooperative formation flight of multi UAV in complex sensing constraints and complex communication environment, putting forward more effective control method and carrying out the UAV physical formation flying test so that the UAV can finish the task better may be the future research directions.
2024, 56(1):1-16.
DOI: 10.11918/202306009
Abstract:
The advent of Industry 4.0 has spawned the widespread application of digital twin technology, providing digital solutions for intelligent manufacturing and product life-cycle management. In the field of civil engineering, the enhancement of digital disaster prevention and civil structure management is a critical component in the development of future smart cities. On one hand, the establishment of precise and reliable digital twins of real-life civil structures can facilitate disaster prevention from extreme hazards, as well as identify and warn against potential risks. On the other hand, digital twins lay the foundation for technological advancements in the digital construction and management of future cities. This study first categorizes the fundamental concepts and developmental stages of digital twin technology. Then, the acquisition of twining data and construction of digital twins for civil structures are systematically summarized. Building on this foundation, a comprehensive review and outlook is presented on the application of digital twin technology in civil engineering, encompassing the operation and maintenance of structures, disaster simulation and digital twin cities.
The advent of Industry 4.0 has spawned the widespread application of digital twin technology, providing digital solutions for intelligent manufacturing and product life-cycle management. In the field of civil engineering, the enhancement of digital disaster prevention and civil structure management is a critical component in the development of future smart cities. On one hand, the establishment of precise and reliable digital twins of real-life civil structures can facilitate disaster prevention from extreme hazards, as well as identify and warn against potential risks. On the other hand, digital twins lay the foundation for technological advancements in the digital construction and management of future cities. This study first categorizes the fundamental concepts and developmental stages of digital twin technology. Then, the acquisition of twining data and construction of digital twins for civil structures are systematically summarized. Building on this foundation, a comprehensive review and outlook is presented on the application of digital twin technology in civil engineering, encompassing the operation and maintenance of structures, disaster simulation and digital twin cities.
2023, 55(5):114-121.
DOI: 10.11918/202109131
Abstract:
The development of advanced nano-integrated circuit processes has led to a decreasing threshold charge in microelectronic devices, resulting in an increased rate of soft errors caused by single-event effects in digital circuits. To enhance the radiation resistance of standard cells in integrated circuits, this paper proposes a NAND gate structure that is resistant to single-event transients (SETs). In the triple well process, by shorting the substrate and source of each NMOS transistor in the pull-down network, the radiation resistance of the NAND gate was effectively improved, and the hardening of the proposed NAND gate became more effective as the number of inputs increased. Particle incidence simulation experiments were performed by Sentaurus TCAD software in hybrid simulation mode. For the NMOS transistor connected to the output node, the three-dimensional physical model that has been calibrated by the process was used, and the Spice model provided by the manufacturer was adopted for other MOS transistors. Simulation results show that the proposed two-input NAND in 40 nm process could reduce the output voltage fluctuation amplitude in three-input cases at the linear energy transfer (LET) value of incidence particle of 10 MeV·cm2/mg. Besides, the effect of immunity to single particle incidence was achieved in the input mode with N2 transistor closed. For the hardened three-input NAND gate, the output voltage disturbance could be reduced by up to 85.4% even in the “worst case”. Therefore, the proposed hardening method for NAND gate has a significant effect against SET.
The development of advanced nano-integrated circuit processes has led to a decreasing threshold charge in microelectronic devices, resulting in an increased rate of soft errors caused by single-event effects in digital circuits. To enhance the radiation resistance of standard cells in integrated circuits, this paper proposes a NAND gate structure that is resistant to single-event transients (SETs). In the triple well process, by shorting the substrate and source of each NMOS transistor in the pull-down network, the radiation resistance of the NAND gate was effectively improved, and the hardening of the proposed NAND gate became more effective as the number of inputs increased. Particle incidence simulation experiments were performed by Sentaurus TCAD software in hybrid simulation mode. For the NMOS transistor connected to the output node, the three-dimensional physical model that has been calibrated by the process was used, and the Spice model provided by the manufacturer was adopted for other MOS transistors. Simulation results show that the proposed two-input NAND in 40 nm process could reduce the output voltage fluctuation amplitude in three-input cases at the linear energy transfer (LET) value of incidence particle of 10 MeV·cm2/mg. Besides, the effect of immunity to single particle incidence was achieved in the input mode with N2 transistor closed. For the hardened three-input NAND gate, the output voltage disturbance could be reduced by up to 85.4% even in the “worst case”. Therefore, the proposed hardening method for NAND gate has a significant effect against SET.
2023, 55(5):14-21.
DOI: 10.11918/202201069
Abstract:
Due to the complex background of ship targets and much irrelevant interference in visual images, it is difficult to conduct ship detection. In addition, there are few datasets for multi-category ship detection and the samples are often unbalanced, which makes the ship target detection performance degraded. Considering the ship detection background interference, an improved YOLOv3 model was proposed by introducing SimAM attention mechanism, which was used to enhance the weight of the ship target in the extracted features and suppress the weight of background interference, thus improving the model detection performance. Meanwhile, strong real-time data augmentation was applied to improve the unbalanced distribution of sample scales, and transfer learning was combined to improve the ship detection accuracy in the condition of a restricted number of samples. The visualization results of extracted features show that the improved model could suppress irrelevant background features, and the abilities of feature extraction and target localization were enhanced. Without introducing additional learnable parameters, the proposed model achieved 96.93% and 71.49% for mAP.5 and mAP.75 on the SeaShips dataset, and detection speed reached 66 frames per second, indicating a good balance between detection accuracy and efficiency. The improved model optimized the target features more effectively compared with the Saliency-aware CNN and eYOLOv3 models, resulting in an improvement of mAP.5 by 9.53% and 9.19%. The mAP.5 for ship type target detection on Singapore Maritime Dataset reached 81.81%, indicating that the proposed model has good generalization performance.
Due to the complex background of ship targets and much irrelevant interference in visual images, it is difficult to conduct ship detection. In addition, there are few datasets for multi-category ship detection and the samples are often unbalanced, which makes the ship target detection performance degraded. Considering the ship detection background interference, an improved YOLOv3 model was proposed by introducing SimAM attention mechanism, which was used to enhance the weight of the ship target in the extracted features and suppress the weight of background interference, thus improving the model detection performance. Meanwhile, strong real-time data augmentation was applied to improve the unbalanced distribution of sample scales, and transfer learning was combined to improve the ship detection accuracy in the condition of a restricted number of samples. The visualization results of extracted features show that the improved model could suppress irrelevant background features, and the abilities of feature extraction and target localization were enhanced. Without introducing additional learnable parameters, the proposed model achieved 96.93% and 71.49% for mAP.5 and mAP.75 on the SeaShips dataset, and detection speed reached 66 frames per second, indicating a good balance between detection accuracy and efficiency. The improved model optimized the target features more effectively compared with the Saliency-aware CNN and eYOLOv3 models, resulting in an improvement of mAP.5 by 9.53% and 9.19%. The mAP.5 for ship type target detection on Singapore Maritime Dataset reached 81.81%, indicating that the proposed model has good generalization performance.
2023, 55(5):107-113.
DOI: 10.11918/202204106
Abstract:
In the ultra-dense network environment, each access point is deployed in the hotspot area, which forms a complex heterogeneous network. Users need to choose the appropriate network to access, so as to achieve the best performance. Network selection problem is to choose the optimal network for the user, so that the user or network performance reaches the best. In order to solve the access selection problem of users in ultra-dense networks, we proposed an ultra-dense network access selection algorithm based on the improved deep Q network (DQN), considering network states, user preferences, and service types, and combining with load balancing strategies. First, by analyzing the influence of network attributes and user preferences on network selection, the appropriate network parameters were selected as the parameters of the access selection algorithm. Then, the problem of network access selection was modeled by Markov decision-making process, and the states, actions, and reward functions of the model were designed. Finally, the optimal network strategy was obtained by using DQN to solve the network selection model. In addition, the target function of traditional DQN was optimized to avoid overestimation of Q value by DQN, and a priority experience replay mechanism was introduced to improve learning efficiency. Simulation results show that the method could well solve the problem of overestimation of traditional DQN, accelerate the convergence of neural network, effectively reduce user congestion, and improve network throughput performance.
In the ultra-dense network environment, each access point is deployed in the hotspot area, which forms a complex heterogeneous network. Users need to choose the appropriate network to access, so as to achieve the best performance. Network selection problem is to choose the optimal network for the user, so that the user or network performance reaches the best. In order to solve the access selection problem of users in ultra-dense networks, we proposed an ultra-dense network access selection algorithm based on the improved deep Q network (DQN), considering network states, user preferences, and service types, and combining with load balancing strategies. First, by analyzing the influence of network attributes and user preferences on network selection, the appropriate network parameters were selected as the parameters of the access selection algorithm. Then, the problem of network access selection was modeled by Markov decision-making process, and the states, actions, and reward functions of the model were designed. Finally, the optimal network strategy was obtained by using DQN to solve the network selection model. In addition, the target function of traditional DQN was optimized to avoid overestimation of Q value by DQN, and a priority experience replay mechanism was introduced to improve learning efficiency. Simulation results show that the method could well solve the problem of overestimation of traditional DQN, accelerate the convergence of neural network, effectively reduce user congestion, and improve network throughput performance.
2023, 55(5):30-38.
DOI: 10.11918/202203059
Abstract:
With the increasing scale of network, the accurate and real-time prediction of network flow is essential for traffic scheduling and routing design. However, due to the nonlinearity and uncertainty of network flow data, some traditional methods fail to achieve good prediction accuracy. Considering the complex spatialtemporal features of network flow, a novel network flow prediction method based on spatialtemporal features fusion (ST-Fusion) was proposed, combined with encoderdecoder architecture. First, the encoder was designed with two parallel feature channels: temporal and spatial channels. The temporal features were extracted by integrating gated recurrent unit (GRU) and self-attention mechanism, and the graph convolutional network (GCN) was used to extract the spatial features. Then, the temporal and spatial features extracted by the encoder were fused by using the bilateral gated mechanism. Finally, the fused features were input into the GRU-based decoder to generate prediction results. Experiments were conducted on three public datasets (GEANT, ABILENE, and CERNET) using evaluation metrics including MAE, RMSE, ACCURACY, and VAR. Experimental results showed that the ST-Fusion method achieved better performance in network flow prediction.
With the increasing scale of network, the accurate and real-time prediction of network flow is essential for traffic scheduling and routing design. However, due to the nonlinearity and uncertainty of network flow data, some traditional methods fail to achieve good prediction accuracy. Considering the complex spatialtemporal features of network flow, a novel network flow prediction method based on spatialtemporal features fusion (ST-Fusion) was proposed, combined with encoderdecoder architecture. First, the encoder was designed with two parallel feature channels: temporal and spatial channels. The temporal features were extracted by integrating gated recurrent unit (GRU) and self-attention mechanism, and the graph convolutional network (GCN) was used to extract the spatial features. Then, the temporal and spatial features extracted by the encoder were fused by using the bilateral gated mechanism. Finally, the fused features were input into the GRU-based decoder to generate prediction results. Experiments were conducted on three public datasets (GEANT, ABILENE, and CERNET) using evaluation metrics including MAE, RMSE, ACCURACY, and VAR. Experimental results showed that the ST-Fusion method achieved better performance in network flow prediction.
2025, 57(7):1-11.
DOI: 10.11918/202312041
Abstract:
In order to accurately analyze the morphological characteristics and distribution properties of aggregates in the mixture, and to have a more comprehensive, in-depth, and specific understanding of aggregates, CT scanning, digital image processing, and three-dimensional geometric reconstruction technologies were used to reconstruct the real shape of aggregate particles. Five morphological characteristic parameters of aggregates were proposed, and a digital evaluation and experimental analysis were conducted on the morphological characteristics of three aggregates. The accuracy of the digital reconstruction method was validated and the morphological distribution characteristics of aggregate particles were analyzed. Additionally, the Pearson correlation method was utilized to analyze the correlations among the morphological parameters. The study demonstrates that the use of CT scanning technology and digital reconstruction technology can accurately restore the morphological characteristics of aggregate particles and obtain morphological parameters. There are significant distribution characteristics of the morphology of different particle sizes of the same aggregate. The three-dimensional needle-like index and three-dimensional texture index show little variation across different particle sizes. As the particle size increases, the variability of the morphology parameter values for aggregates decreases. The overall three-dimensional texture index follows a power-law distribution, and the complexity gradually decreases with the increase of particle size. Additionally, as the particle size increases, the three-dimensional edge angle gradually stabilizes. There is a strong negative correlation between three-dimensional edge angle and solid moment degree, as well as between solid sphericity and three-dimensional edge angle. Conversely, there is a strong positive correlation between sphericity of the actual shape and the three-dimensional texture index. Digital 3D reconstruction can accurately and comprehensively describes and analyzes the morphology and distribution characteristics of aggregates.
In order to accurately analyze the morphological characteristics and distribution properties of aggregates in the mixture, and to have a more comprehensive, in-depth, and specific understanding of aggregates, CT scanning, digital image processing, and three-dimensional geometric reconstruction technologies were used to reconstruct the real shape of aggregate particles. Five morphological characteristic parameters of aggregates were proposed, and a digital evaluation and experimental analysis were conducted on the morphological characteristics of three aggregates. The accuracy of the digital reconstruction method was validated and the morphological distribution characteristics of aggregate particles were analyzed. Additionally, the Pearson correlation method was utilized to analyze the correlations among the morphological parameters. The study demonstrates that the use of CT scanning technology and digital reconstruction technology can accurately restore the morphological characteristics of aggregate particles and obtain morphological parameters. There are significant distribution characteristics of the morphology of different particle sizes of the same aggregate. The three-dimensional needle-like index and three-dimensional texture index show little variation across different particle sizes. As the particle size increases, the variability of the morphology parameter values for aggregates decreases. The overall three-dimensional texture index follows a power-law distribution, and the complexity gradually decreases with the increase of particle size. Additionally, as the particle size increases, the three-dimensional edge angle gradually stabilizes. There is a strong negative correlation between three-dimensional edge angle and solid moment degree, as well as between solid sphericity and three-dimensional edge angle. Conversely, there is a strong positive correlation between sphericity of the actual shape and the three-dimensional texture index. Digital 3D reconstruction can accurately and comprehensively describes and analyzes the morphology and distribution characteristics of aggregates.
2024, 56(1):63-72.
DOI: 10.11918/202206110
Abstract:
To improve the ductility of steelultra-high performance concrete (UHPC) composite structures, we proposed a type of demountable steelUHPC composite slab based on demountable shear connectors. The flexural tests for demountable steelUHPC composite slabs with different shear connection degrees were designed and completed. The failure mode, ultimate capacity, stiffness, cracking behavior, and relative slip of demountable steelUHPC composite slabs were analyzed and compared with those of steelUHPC composite slabs with welded shear connectors. The demountability of demountable steelUHPC composite slabs was discussed. The ultimate flexural capacity and flexural stiffness of demountable steelUHPC composite slabs were theoretically analyzed, and related calculation formulas were deduced. Results showed that the failure mode of demountable steelUHPC composite slabs was longitudinal horizontal shear bonding failure. Reducing the stud spacing could enhance the cooperative deformation capacity of demountable steelUHPC composite slabs, resulting in the improvement of their ultimate flexural capacity, stiffness at the elastic-plastic stage, and crack control ability. Different from the steelUHPC composite slabs with welded shear connectors, the steel slab and UHPC slab of the demountable steelUHPC composite slabs could be easily disassembled even in the condition of large deformation. The formulas for the ultimate flexural capacity and flexural stiffness of demountable steelUHPC composite slabs were derived. It was proposed that the height of UHPC slab should be reduced when calculating the flexural stiffness, and the reduction coefficient (βU) was suggested to be 0.85 in serviceability state. The theoretical calculation results were in good agreement with the test results. The research results can provide theoretical basis for the design and application of steelUHPC composite slabs with demountable shear connectors.
To improve the ductility of steelultra-high performance concrete (UHPC) composite structures, we proposed a type of demountable steelUHPC composite slab based on demountable shear connectors. The flexural tests for demountable steelUHPC composite slabs with different shear connection degrees were designed and completed. The failure mode, ultimate capacity, stiffness, cracking behavior, and relative slip of demountable steelUHPC composite slabs were analyzed and compared with those of steelUHPC composite slabs with welded shear connectors. The demountability of demountable steelUHPC composite slabs was discussed. The ultimate flexural capacity and flexural stiffness of demountable steelUHPC composite slabs were theoretically analyzed, and related calculation formulas were deduced. Results showed that the failure mode of demountable steelUHPC composite slabs was longitudinal horizontal shear bonding failure. Reducing the stud spacing could enhance the cooperative deformation capacity of demountable steelUHPC composite slabs, resulting in the improvement of their ultimate flexural capacity, stiffness at the elastic-plastic stage, and crack control ability. Different from the steelUHPC composite slabs with welded shear connectors, the steel slab and UHPC slab of the demountable steelUHPC composite slabs could be easily disassembled even in the condition of large deformation. The formulas for the ultimate flexural capacity and flexural stiffness of demountable steelUHPC composite slabs were derived. It was proposed that the height of UHPC slab should be reduced when calculating the flexural stiffness, and the reduction coefficient (βU) was suggested to be 0.85 in serviceability state. The theoretical calculation results were in good agreement with the test results. The research results can provide theoretical basis for the design and application of steelUHPC composite slabs with demountable shear connectors.
2023, 55(5):1-13.
DOI: 10.11918/202206056
Abstract:
In view of the weaknesses of poor computing and storage capabilities of edge devices, lightweight processing was carried out on the backbone network CSPDarkNet53 for feature extraction in the traditional YOLOv5 model, and a lightweight gesture recognition algorithm MPE-YOLOv5 was proposed to realize the deployment of the model in low-power edge devices. Considering the problem that it is difficult to identify large-scale transformation targets and tiny targets due to less feature extraction in lightweight model, efficient channel attention (ECA) mechanism was added to alleviate the loss of information after high-level feature mapping due to the reduction of feature channel. A detection layer for tiny targets was added to improve the sensitivity to tiny target gestures. EIoU was selected as the loss function of the detection frame to improve the positioning accuracy. The effectiveness of the MPE-YOLOv5 algorithm was verified on the self-made dataset and NUS-Ⅱ public dataset, and the MPE-YOLOv5 algorithm was compared with lightweight M-YOLOv5 algorithm and original YOLOv5 algorithm on the self-made dataset. Experimental results show that the model parameters, model size, and computational complexity of the improved algorithm were 21.16%, 25.33%, and 27.33% of the original algorithm, and the average accuracy was 97.2%. Compared with the lightweight model M-YOLOv5, MPE-YOLOv5 improved the average accuracy by 8.72% while maintaining the original efficiency. The proposed MPE-YOLOv5 algorithm can better balance between the detection accuracy and real-time reasoning speed of the model, and can be deployed on edge terminals with limited hardware.
In view of the weaknesses of poor computing and storage capabilities of edge devices, lightweight processing was carried out on the backbone network CSPDarkNet53 for feature extraction in the traditional YOLOv5 model, and a lightweight gesture recognition algorithm MPE-YOLOv5 was proposed to realize the deployment of the model in low-power edge devices. Considering the problem that it is difficult to identify large-scale transformation targets and tiny targets due to less feature extraction in lightweight model, efficient channel attention (ECA) mechanism was added to alleviate the loss of information after high-level feature mapping due to the reduction of feature channel. A detection layer for tiny targets was added to improve the sensitivity to tiny target gestures. EIoU was selected as the loss function of the detection frame to improve the positioning accuracy. The effectiveness of the MPE-YOLOv5 algorithm was verified on the self-made dataset and NUS-Ⅱ public dataset, and the MPE-YOLOv5 algorithm was compared with lightweight M-YOLOv5 algorithm and original YOLOv5 algorithm on the self-made dataset. Experimental results show that the model parameters, model size, and computational complexity of the improved algorithm were 21.16%, 25.33%, and 27.33% of the original algorithm, and the average accuracy was 97.2%. Compared with the lightweight model M-YOLOv5, MPE-YOLOv5 improved the average accuracy by 8.72% while maintaining the original efficiency. The proposed MPE-YOLOv5 algorithm can better balance between the detection accuracy and real-time reasoning speed of the model, and can be deployed on edge terminals with limited hardware.
2024, 56(1):117-129.
DOI: 10.11918/202302046
Abstract:
To study the mechanical performance of concrete-filled double-skin steel tubular long columns under compressive and torsional loads, two ordinary circular steel tube reinforced concrete columns and two double-layered steel tube reinforced concrete columns were subjected to low-cycle reciprocating tests under pure torsion and torsion-compression loading using a developed Stewart six-degree-of-freedom loading platform. Based on the tests, the bearing capacity, torsional deformation, energy dissipation, and hysteresis performance of each specimen were compared and analyzed, and finite element parameter analysis was conducted. The study shows that both ordinary circular steel tube reinforced concrete columns and double-layered circular steel tube reinforced concrete columns have good torsional resistance. Compared with ordinary circular steel tube reinforced concrete columns, the initial stiffness and bearing capacity of double-layered steel tube reinforced concrete columns are slightly improved, the hysteresis curve is more full, and the energy dissipation capacity and ductility are greatly improved. Parameter analysis shows that when the steel content is constant, the larger the thickness ratio of the inner steel tube, the more beneficial it is for torsional resistance; and within a certain range of axial loads, the torsional resistance of steel tube reinforced concrete columns can be improved.
To study the mechanical performance of concrete-filled double-skin steel tubular long columns under compressive and torsional loads, two ordinary circular steel tube reinforced concrete columns and two double-layered steel tube reinforced concrete columns were subjected to low-cycle reciprocating tests under pure torsion and torsion-compression loading using a developed Stewart six-degree-of-freedom loading platform. Based on the tests, the bearing capacity, torsional deformation, energy dissipation, and hysteresis performance of each specimen were compared and analyzed, and finite element parameter analysis was conducted. The study shows that both ordinary circular steel tube reinforced concrete columns and double-layered circular steel tube reinforced concrete columns have good torsional resistance. Compared with ordinary circular steel tube reinforced concrete columns, the initial stiffness and bearing capacity of double-layered steel tube reinforced concrete columns are slightly improved, the hysteresis curve is more full, and the energy dissipation capacity and ductility are greatly improved. Parameter analysis shows that when the steel content is constant, the larger the thickness ratio of the inner steel tube, the more beneficial it is for torsional resistance; and within a certain range of axial loads, the torsional resistance of steel tube reinforced concrete columns can be improved.
SHI Jingzhou
,
ZHOU Lingyu
,
FANG Jiaopeng
,
LIU Xiaochun
,
LIU Jiahao
,
HE Changjie
,
LI Fengui
,
DAI Chaohu
,
LIAO Fei
,
WU Ruizhi
2024, 56(1):73-83.
DOI: 10.11918/202305009
Abstract:
In order to give full play to the advantages of the high degree of industrialization of assembly and the excellent mechanical properties of steel-concrete composite structures, a kind of assembled double-slotted channel steel-concrete composite floor slab was proposed. Three groups of simply supported composite floor slab specimens were tested under four-point loading, and the mechanical properties of the composite floor slab under vertical static load were studied. The development law of floor cracks, deflection and strain (steel bar, steel beam, concrete slab) with load was analyzed. Based on the limit equilibrium method, the bearing capacity calculation formula considering the tensile membrane effect and stiffness strengthening coefficient was proposed. The results showed that the deformation of the composite slab is characterized by two-way slab. When the specimens are destroyed, the corner cracks and arc cracks appear on the top of the slab, the central area of the concrete slab bottom shows mesh cracks and oblique cracks extending to the corner, and the plastic bending of the double main girder occurs. When the center deflection of the floor reaches l0/40, the load of the specimens is 327.63 kN, 436.92 kN and 406.12 kN respectively, and the bearing capacity of the composite floor is higher. The strain development of the steel bar is larger in the direction perpendicular to the steel beam and yields along the plastic hinge line. The calculation formula considering the tensile membrane effect and the stiffness strengthening coefficient is in good agreement with the test results, and the load-deflection curve of the floor is accurately predicted.
In order to give full play to the advantages of the high degree of industrialization of assembly and the excellent mechanical properties of steel-concrete composite structures, a kind of assembled double-slotted channel steel-concrete composite floor slab was proposed. Three groups of simply supported composite floor slab specimens were tested under four-point loading, and the mechanical properties of the composite floor slab under vertical static load were studied. The development law of floor cracks, deflection and strain (steel bar, steel beam, concrete slab) with load was analyzed. Based on the limit equilibrium method, the bearing capacity calculation formula considering the tensile membrane effect and stiffness strengthening coefficient was proposed. The results showed that the deformation of the composite slab is characterized by two-way slab. When the specimens are destroyed, the corner cracks and arc cracks appear on the top of the slab, the central area of the concrete slab bottom shows mesh cracks and oblique cracks extending to the corner, and the plastic bending of the double main girder occurs. When the center deflection of the floor reaches l0/40, the load of the specimens is 327.63 kN, 436.92 kN and 406.12 kN respectively, and the bearing capacity of the composite floor is higher. The strain development of the steel bar is larger in the direction perpendicular to the steel beam and yields along the plastic hinge line. The calculation formula considering the tensile membrane effect and the stiffness strengthening coefficient is in good agreement with the test results, and the load-deflection curve of the floor is accurately predicted.
2023, 55(5):78-87.
DOI: 10.11918/202112059
Abstract:
Considering the failure mechanism and weaknesses of traditional fabricated shear wall structures under strong earthquakes, a new type of fabricated shear wall with functions of energy dissipation and shock absorption was proposed. On the basis of model test and numerical simulation, seismic performance tests were carried out on four specimens with scale ratio of 1∶1.54 and shear span ratio of 1.52. Further analysis was conducted to investigate the effects of bolt number, axial compression ratio, and reinforcement ratio of edge members on the seismic performance of the new fabricated shear wall, including failure modes, hysteretic performance, bearing capacity, displacement ductility, stiffness degradation, and energy dissipation capacity. Test results show that the four specimens experienced shear compression failure, which was the same as the cast-in-place shear wall with the same shear span ratio. However, the proposed shear wall had better hysteretic performance and energy dissipation capacity, and the energy dissipation capacity was higher than that of the cast-in-place shear wall at the failure point. When the number of bolts decreased, the hysteretic performance of the new fabricated shear wall decreased, the wall deformation increased, while the bearing capacity remained almost unchanged. When the axial compression ratio or reinforcement ratio of edge members decreased, the bearing capacity decreased, and the ultimate displacement increased. Finally, the finite element model of the specimens was established by ABAQUS program. Comparisons of numerical results and test results showed a good agreement, verifying the correctness of the model, which can be applied to the analysis of the new fabricated shear wall.
Considering the failure mechanism and weaknesses of traditional fabricated shear wall structures under strong earthquakes, a new type of fabricated shear wall with functions of energy dissipation and shock absorption was proposed. On the basis of model test and numerical simulation, seismic performance tests were carried out on four specimens with scale ratio of 1∶1.54 and shear span ratio of 1.52. Further analysis was conducted to investigate the effects of bolt number, axial compression ratio, and reinforcement ratio of edge members on the seismic performance of the new fabricated shear wall, including failure modes, hysteretic performance, bearing capacity, displacement ductility, stiffness degradation, and energy dissipation capacity. Test results show that the four specimens experienced shear compression failure, which was the same as the cast-in-place shear wall with the same shear span ratio. However, the proposed shear wall had better hysteretic performance and energy dissipation capacity, and the energy dissipation capacity was higher than that of the cast-in-place shear wall at the failure point. When the number of bolts decreased, the hysteretic performance of the new fabricated shear wall decreased, the wall deformation increased, while the bearing capacity remained almost unchanged. When the axial compression ratio or reinforcement ratio of edge members decreased, the bearing capacity decreased, and the ultimate displacement increased. Finally, the finite element model of the specimens was established by ABAQUS program. Comparisons of numerical results and test results showed a good agreement, verifying the correctness of the model, which can be applied to the analysis of the new fabricated shear wall.
2024, 56(1):130-138.
DOI: 10.11918/202209006
Abstract:
To improve the construction efficiency of building envelope and solve the long-term problems of falling off and ignition of traditional external insulation systems, a kind of rock wool composite insulation external formwork (RWCIEF) system integrating insulation and building formwork was proposed. The RWCIEF structure from inside to outside was designed as follows: inner reinforcing layer, rock wool insulation core material, adhesive layer, insulation transition layer, and outer reinforcing layer. Taking Harbin as an example, the optimal thickness of rock wool insulation core material was determined based on the life cycle cost (Clc). The feasibility of RWCIEF in engineering was explored by combining finite element analysis with theoretical calculation. The bending properties, construction bearing capacity, and stress and deformation under temperature effect of RWCIEF were calculated and analyzed. The influences of groove form, groove width, groove depth, and groove spacing on the bending properties of RWCIEF were discussed. Results showed that the theoretical calculation results of bending properties of RWCIEF were in good agreement with the finite element analysis results. The grooving treatment effectively improved the bending properties of RWCIEF. Considering the bending properties, thermal characteristics, and processing angle, groove forms of symmetrical cross grooves or symmetrical longitudinal grooves were suggested, with the groove depth and width of 10 mm and the groove spacing of 150 mm. The designed RWCIEF met the construction bearing capacity and could fully guarantee the construction quality of the thermal insulation works of the outer enclosure structure. The maximum tensile stress and compressive stress caused by temperature effect did not exceed the bearing capacity of the outer reinforcing layer of RWCIEF, which indicates that RWCIEF is unlikely to hollow in summer or crack in winter. The proposed RWCIEF system can provide a new idea and method for the future research directions of exterior envelope insulation and building formwork engineering.
To improve the construction efficiency of building envelope and solve the long-term problems of falling off and ignition of traditional external insulation systems, a kind of rock wool composite insulation external formwork (RWCIEF) system integrating insulation and building formwork was proposed. The RWCIEF structure from inside to outside was designed as follows: inner reinforcing layer, rock wool insulation core material, adhesive layer, insulation transition layer, and outer reinforcing layer. Taking Harbin as an example, the optimal thickness of rock wool insulation core material was determined based on the life cycle cost (Clc). The feasibility of RWCIEF in engineering was explored by combining finite element analysis with theoretical calculation. The bending properties, construction bearing capacity, and stress and deformation under temperature effect of RWCIEF were calculated and analyzed. The influences of groove form, groove width, groove depth, and groove spacing on the bending properties of RWCIEF were discussed. Results showed that the theoretical calculation results of bending properties of RWCIEF were in good agreement with the finite element analysis results. The grooving treatment effectively improved the bending properties of RWCIEF. Considering the bending properties, thermal characteristics, and processing angle, groove forms of symmetrical cross grooves or symmetrical longitudinal grooves were suggested, with the groove depth and width of 10 mm and the groove spacing of 150 mm. The designed RWCIEF met the construction bearing capacity and could fully guarantee the construction quality of the thermal insulation works of the outer enclosure structure. The maximum tensile stress and compressive stress caused by temperature effect did not exceed the bearing capacity of the outer reinforcing layer of RWCIEF, which indicates that RWCIEF is unlikely to hollow in summer or crack in winter. The proposed RWCIEF system can provide a new idea and method for the future research directions of exterior envelope insulation and building formwork engineering.
2025, 57(9):1-10.
DOI: 10.11918/202407049
Abstract:
To analyze the saturation and coupling characteristics of SynRM and realize inductance identification with small disturbance and low error, an online inductance decoupling identification algorithm for SynRM is proposed. The influence of magnetic saturation and coupling on the voltage and flux linkage equations is first described to interpret the saturation and coupling characteristics of the inductance, and a decoupling motor model is developed by introducing a coupling angle. This model enables the analysis of saturation and coupling effects from a decoupling perspective. Then, an online identification strategy based on a virtual-axis equivalent impedance model is designed to identify both the coupling angle and inductance in real time. The proposed method is validated on a 3 kW SynRM experimental platform under various operating conditions. Experimental results demonstrate that the proposed algorithm effectively realizes online inductance decoupling identification, with identification errors for both the coupling angle and inductance within acceptable limits. Moreover, the inductance decreases with the increase of current, and the coupling angle increases with the increase of current. The changing trends of coupling angle and inductance identification results also verify the accuracy of motor saturation and coupling characteristic analysis. Compared to other inductance identification algorithms, the proposed algorithm does not require high chip computing power. While simplifying inductance calculations, it can also follow motor control in real time and output accurate values.
To analyze the saturation and coupling characteristics of SynRM and realize inductance identification with small disturbance and low error, an online inductance decoupling identification algorithm for SynRM is proposed. The influence of magnetic saturation and coupling on the voltage and flux linkage equations is first described to interpret the saturation and coupling characteristics of the inductance, and a decoupling motor model is developed by introducing a coupling angle. This model enables the analysis of saturation and coupling effects from a decoupling perspective. Then, an online identification strategy based on a virtual-axis equivalent impedance model is designed to identify both the coupling angle and inductance in real time. The proposed method is validated on a 3 kW SynRM experimental platform under various operating conditions. Experimental results demonstrate that the proposed algorithm effectively realizes online inductance decoupling identification, with identification errors for both the coupling angle and inductance within acceptable limits. Moreover, the inductance decreases with the increase of current, and the coupling angle increases with the increase of current. The changing trends of coupling angle and inductance identification results also verify the accuracy of motor saturation and coupling characteristic analysis. Compared to other inductance identification algorithms, the proposed algorithm does not require high chip computing power. While simplifying inductance calculations, it can also follow motor control in real time and output accurate values.
2023, 55(5):59-70.
DOI: 10.11918/202204057
Abstract:
Image segmentation is to divide the region with special meanings into several disjoint sub-regions according to certain rules, which is the key link between image processing and image analysis. The traditional watershed image segmentation method is widely used, which has the advantages of fast and simple. However, it is easily interfered by noise, and the segmentation results are prone to lose important edge information, resulting in over-segmentation. In view of the problem of the traditional watershed image segmentation method, an improved watershed image segmentation method based on adaptive structural elements was proposed. First, the adaptive structural elements with variable shapes were constructed by using local density, symmetry, and boundary features of adjacent pixels of image targets, so as to ensure a good consistency between the proposed structural elements and the shape of image targets. Then, the adaptive structural elements were used to obtain the morphological gradient of the image, which could improve the positioning accuracy of the target edge. The L0 norm gradient minimization and morphological open-close hybrid reconstruction were used to modify the gradient image, so as to reduce the local invalid minimum points in the gradient image and suppress the occurrence of over-segmentation. Finally, watershed segmentation was performed on the modified gradient image to realize accurate segmentation of the target region of the image. Experimental results show that the method could effectively restrain over-segmentation of traditional watershed algorithm and improve the accuracy of the target edge positioning, with high precision of image segmentation.
Image segmentation is to divide the region with special meanings into several disjoint sub-regions according to certain rules, which is the key link between image processing and image analysis. The traditional watershed image segmentation method is widely used, which has the advantages of fast and simple. However, it is easily interfered by noise, and the segmentation results are prone to lose important edge information, resulting in over-segmentation. In view of the problem of the traditional watershed image segmentation method, an improved watershed image segmentation method based on adaptive structural elements was proposed. First, the adaptive structural elements with variable shapes were constructed by using local density, symmetry, and boundary features of adjacent pixels of image targets, so as to ensure a good consistency between the proposed structural elements and the shape of image targets. Then, the adaptive structural elements were used to obtain the morphological gradient of the image, which could improve the positioning accuracy of the target edge. The L0 norm gradient minimization and morphological open-close hybrid reconstruction were used to modify the gradient image, so as to reduce the local invalid minimum points in the gradient image and suppress the occurrence of over-segmentation. Finally, watershed segmentation was performed on the modified gradient image to realize accurate segmentation of the target region of the image. Experimental results show that the method could effectively restrain over-segmentation of traditional watershed algorithm and improve the accuracy of the target edge positioning, with high precision of image segmentation.
2016, 48(4):1-12.
DOI: 10.11918/j.issn.0367-6234.2016.04.001
Abstract:
Autonomous navigation based on sequential images (ANBSI) is the key technology of pinpoint landing missions for future deep space exploration and also is one of the major development directions for deep space exploration technology. The necessity of developing ANBSI for planetary pinpoint landing is elaborated in this paper. Firstly, state-of-art developments of ANBSI are reviewed in terms of active sensing and passive sensing. Then, the key techniques applied in ANBSI for planetary landing are summarized and analyzed. Finally, according to the analysis of the key techniques, the main issues of ANBSI are raised and their future developments are overviewed.
Autonomous navigation based on sequential images (ANBSI) is the key technology of pinpoint landing missions for future deep space exploration and also is one of the major development directions for deep space exploration technology. The necessity of developing ANBSI for planetary pinpoint landing is elaborated in this paper. Firstly, state-of-art developments of ANBSI are reviewed in terms of active sensing and passive sensing. Then, the key techniques applied in ANBSI for planetary landing are summarized and analyzed. Finally, according to the analysis of the key techniques, the main issues of ANBSI are raised and their future developments are overviewed.
2023, 55(5):88-97.
DOI: 10.11918/202111001
Abstract:
In view of the problems of low brightness and obvious color distortion of the sky in restored images in most existing algorithms for image dehazing, a haze removal method for UAV aerial images based on atmospheric light value and graph estimation was proposed. First, the depth-of-field image was obtained according to the color attenuation prior theory, and the mean value of the region with the minimum deviation in the depth-of-field image was taken as the atmospheric light value. Then, a random walk clustering method was designed to estimate the atmospheric light map. The random walk algorithm was used to cluster the image into N sub-regions, and the mean value of the first 0.1% pixels of the sub-regions was taken as the regional atmospheric light value, which was then combined and refined by guided filtering to obtain the atmospheric light map. Next, the two atmospheric light estimators were fused into a new atmospheric light map with atmospheric light valuegraph estimation, which is a more accurate atmospheric light estimator. The transmittance was obtained by haze-lines prior method, and a dark compensation method was proposed to improve the transmission accuracy. Finally, according to the atmospheric scattering model, a clear restored image was obtained based on the fused atmospheric light map and optimized transmittance. Experimental results show that compared with other algorithms, the proposed algorithm improved the information entropy, mean gradient, blur coefficient, and contrast by 1.1%, 6.3%, 8.5%, and 6.4%, respectively, with better subjective visual effect and more abundant information.
In view of the problems of low brightness and obvious color distortion of the sky in restored images in most existing algorithms for image dehazing, a haze removal method for UAV aerial images based on atmospheric light value and graph estimation was proposed. First, the depth-of-field image was obtained according to the color attenuation prior theory, and the mean value of the region with the minimum deviation in the depth-of-field image was taken as the atmospheric light value. Then, a random walk clustering method was designed to estimate the atmospheric light map. The random walk algorithm was used to cluster the image into N sub-regions, and the mean value of the first 0.1% pixels of the sub-regions was taken as the regional atmospheric light value, which was then combined and refined by guided filtering to obtain the atmospheric light map. Next, the two atmospheric light estimators were fused into a new atmospheric light map with atmospheric light valuegraph estimation, which is a more accurate atmospheric light estimator. The transmittance was obtained by haze-lines prior method, and a dark compensation method was proposed to improve the transmission accuracy. Finally, according to the atmospheric scattering model, a clear restored image was obtained based on the fused atmospheric light map and optimized transmittance. Experimental results show that compared with other algorithms, the proposed algorithm improved the information entropy, mean gradient, blur coefficient, and contrast by 1.1%, 6.3%, 8.5%, and 6.4%, respectively, with better subjective visual effect and more abundant information.
2024, 56(1):84-92.
DOI: 10.11918/202208008
Abstract:
In order to investigate the flexural behavior of ultra-high performance concrete (UHPC) lightweight composite decks under local wheel load, four demountable steelUHPC composite slabs connected by high-strength bolts were designed and four-point bending test was conducted. The influence of steel plate type and spacing of shear connector on the flexural characteristics of demountable steelUHPC composite slabs was analyzed, including failure mode, load-deflection curve, interface relative slip, crack width, and sectional strain distribution. Results showed that under positive bending moment, the failure mode of composite slabs adopting Q355 steel plate was that the high-strength bolt was cut off. While the failure mode of composite slabs using steel plate with negative Poisson’s ratio (NPR) was as follows: part of high-strength bolts was cut off, part of pre-embedded elongated nuts with cushion was pulled out, and UHPC collapsed due to instantaneous instability. Besides, under the same spacing of high-strength bolts, the relative slip of plate end of composite slabs employing NPR steel plate was relatively small, indicating that NPR steel plate can effectively delay and restrain the relative slip between steel plate and UHPC plate, thus improving the synergistic deformation capacity, flexural stiffness, and flexural bearing capacity for composite slabs. According to the sectional strain distribution analysis, due to the negative Poisson’s ratio effect, high stiffness, and high yield strength of NPR steel plate, the tensile strain between NPR steel plate and the bottom UHPC layer maintained strain compatibility during the whole loading process, and the upward displacement for sectional plastic neutral axis could be ignored with increasing load. Therefore, under the premise that NPR steel plate is employed to improve the flexural performance of steelUHPC composite slab system, the thickness of UHPC should be reasonably matched with the performance of NPR steel plate, so as to give full play to their material properties, and avoid the buckling failure prior to the material strength failure of UHPC.
In order to investigate the flexural behavior of ultra-high performance concrete (UHPC) lightweight composite decks under local wheel load, four demountable steelUHPC composite slabs connected by high-strength bolts were designed and four-point bending test was conducted. The influence of steel plate type and spacing of shear connector on the flexural characteristics of demountable steelUHPC composite slabs was analyzed, including failure mode, load-deflection curve, interface relative slip, crack width, and sectional strain distribution. Results showed that under positive bending moment, the failure mode of composite slabs adopting Q355 steel plate was that the high-strength bolt was cut off. While the failure mode of composite slabs using steel plate with negative Poisson’s ratio (NPR) was as follows: part of high-strength bolts was cut off, part of pre-embedded elongated nuts with cushion was pulled out, and UHPC collapsed due to instantaneous instability. Besides, under the same spacing of high-strength bolts, the relative slip of plate end of composite slabs employing NPR steel plate was relatively small, indicating that NPR steel plate can effectively delay and restrain the relative slip between steel plate and UHPC plate, thus improving the synergistic deformation capacity, flexural stiffness, and flexural bearing capacity for composite slabs. According to the sectional strain distribution analysis, due to the negative Poisson’s ratio effect, high stiffness, and high yield strength of NPR steel plate, the tensile strain between NPR steel plate and the bottom UHPC layer maintained strain compatibility during the whole loading process, and the upward displacement for sectional plastic neutral axis could be ignored with increasing load. Therefore, under the premise that NPR steel plate is employed to improve the flexural performance of steelUHPC composite slab system, the thickness of UHPC should be reasonably matched with the performance of NPR steel plate, so as to give full play to their material properties, and avoid the buckling failure prior to the material strength failure of UHPC.
