The study of river dynamics requires knowledge of physical parameters, such as porosity, permeability, and wave propagation velocity, of river-bottom sediments. To do so, sediment properties are determined on mechanic...The study of river dynamics requires knowledge of physical parameters, such as porosity, permeability, and wave propagation velocity, of river-bottom sediments. To do so, sediment properties are determined on mechanically sampled specimens and from subbottom profiling. However, mechanical sampling introduces disturbances that affect test results, with the exception of grain-size distribution. In this study, we perform inversion of acoustic data using the grain-size distribution of mechanically sampled specimens and the relation between porosity and permeability from the Kozeny-Carman equation as prior information. The wave reflection coefficient of the water-silt interface is extracted from the raw subbottom profile. Based on the effective density fluid model, we combine the Kozeny-Carman equation and the wave reflection coefficient. We use experimental data from two Yellow River reservoirs to obtain the wave velocity and density of multiple sections and their spatial variations, and find that the inversion and testing results are in good agreement.展开更多
In this work,an adaptive sampling control strategy for distributed predictive control is proposed.According to the proposed method,the sampling rate of each subsystem of the accused object is determined based on the p...In this work,an adaptive sampling control strategy for distributed predictive control is proposed.According to the proposed method,the sampling rate of each subsystem of the accused object is determined based on the periodic detection of its dynamic behavior and calculations made using a correlation function.Then,the optimal sampling interval within the period is obtained and sent to the corresponding sub-prediction controller,and the sampling interval of the controller is changed accordingly before the next sampling period begins.In the next control period,the adaptive sampling mechanism recalculates the sampling rate of each subsystem’s measurable output variable according to both the abovementioned method and the change in the dynamic behavior of the entire system,and this process is repeated.Such an adaptive sampling interval selection based on an autocorrelation function that measures dynamic behavior can dynamically optimize the selection of sampling rate according to the real-time change in the dynamic behavior of the controlled object.It can also accurately capture dynamic changes,meaning that each sub-prediction controller can more accurately calculate the optimal control quantity at the next moment,significantly improving the performance of distributed model predictive control(DMPC).A comparison demonstrates that the proposed adaptive sampling DMPC algorithm has better tracking performance than the traditional DMPC algorithm.展开更多
Solid particle erosion on the material surfaces is a very common phenomenon in the industrial field,which greatly affects the efficiency,service life,and even poses a great threat to life safety.However,current resear...Solid particle erosion on the material surfaces is a very common phenomenon in the industrial field,which greatly affects the efficiency,service life,and even poses a great threat to life safety.However,current research on erosion resistance is not only inefficient,but also limited to the improvement of hardness and toughness of materials.Inspired by typical scorpion(Parabuthus transvaalicus),biomimetic functional samples with exquisite anti-rosion structures were manufactured.Macroscopic morphology and structure of the biological prototype were analyzed and measured.According to above analysis,combined with response surface methodology,a set of biomimetic samples with different structural parameters were fabricated by using 3D printing technology.The anti-crosion performance of these biomimetic samples was investigated using a blasting jet machine.Based on the results of blasting jet test,as well as regression analysis and fiting,the optimal structural parameters were obtained.In addition to the static test conditions,the optimal biomimetic sample was also eroded in rotating condition and showed excellent erosion resistance property.The presence of bump and groove structures,on the one hand,reduced the croded area of biominetic sample surface.On the other hand,they made the airlow turbulent and consequently reduced the impact cnergy of solid particles,which significantly improved the erosion resistance of biomimetic materials.This study provides a new strategy to improvethe service life of components easily affected by erosion in the aviation,energy and military fields.展开更多
The precise and timely extraction of railway signals is crucial for the creation of railway electronic maps.This paper introduces a novel real-time detection approach for dynamically adjusting railway signals,leveragi...The precise and timely extraction of railway signals is crucial for the creation of railway electronic maps.This paper introduces a novel real-time detection approach for dynamically adjusting railway signals,leveraging an enhanced Real-Time DEtection TRansformer(RT-DETR)model.The enhancement involves the integration of a vision Transformer with Dynamically Quantifiable Sampling Attention Mechanism(DQSAM)into the ResNet50 backbone of the RT-DETR framework,thereby enhancing the model’s efficiency and accuracy in handling intricate visual tasks.Secondly,an ultra-lightweight and effective Dynamic Grouping upSampler(DyGSample)is inserted into the efficient hybrid encode module as the up-sampling part.This operator can effectively upsample the feature graph without increasing the computational burden,and improve the model resolution and detail capture ability.In addition,in order to solve the problem of deep layer of model network and high operating cost,a new bounding box similarity loss function of rotation intersection over union based on minimum point distance is adopted in this paper,which takes into account all relevant factors of existing loss functions,namely overlapping or non-overlapping regions,center point distance,width and height deviation,and simplifies the calculation process.As a lightweight signal detection model with ultra-fast,high real-time,and high precision,the detection accuracy of this method is improved from 90.21%to 97.45%,which proves the superior performance and effectiveness of the improved real-time dynamic adjustment RT-DETR model in railway signal extraction.展开更多
基金supported by the Ministry of Water Resources Special Funds for Scientific Research on Public Causes(No.201301024)the Special Funds for Yellow River Institute of Hydraulic Research(No.HKY-JBYW-2016-09 and No.HKYJBYW-2016-29)
文摘The study of river dynamics requires knowledge of physical parameters, such as porosity, permeability, and wave propagation velocity, of river-bottom sediments. To do so, sediment properties are determined on mechanically sampled specimens and from subbottom profiling. However, mechanical sampling introduces disturbances that affect test results, with the exception of grain-size distribution. In this study, we perform inversion of acoustic data using the grain-size distribution of mechanically sampled specimens and the relation between porosity and permeability from the Kozeny-Carman equation as prior information. The wave reflection coefficient of the water-silt interface is extracted from the raw subbottom profile. Based on the effective density fluid model, we combine the Kozeny-Carman equation and the wave reflection coefficient. We use experimental data from two Yellow River reservoirs to obtain the wave velocity and density of multiple sections and their spatial variations, and find that the inversion and testing results are in good agreement.
基金the National Natural Science Foundation of China(61563032,61963025)The Open Foundation of the Key Laboratory of Gansu Advanced Control for Industrial Processes(2019KX01)The Project of Industrial support and guidance of Colleges and Universities in Gansu Province(2019C05).
文摘In this work,an adaptive sampling control strategy for distributed predictive control is proposed.According to the proposed method,the sampling rate of each subsystem of the accused object is determined based on the periodic detection of its dynamic behavior and calculations made using a correlation function.Then,the optimal sampling interval within the period is obtained and sent to the corresponding sub-prediction controller,and the sampling interval of the controller is changed accordingly before the next sampling period begins.In the next control period,the adaptive sampling mechanism recalculates the sampling rate of each subsystem’s measurable output variable according to both the abovementioned method and the change in the dynamic behavior of the entire system,and this process is repeated.Such an adaptive sampling interval selection based on an autocorrelation function that measures dynamic behavior can dynamically optimize the selection of sampling rate according to the real-time change in the dynamic behavior of the controlled object.It can also accurately capture dynamic changes,meaning that each sub-prediction controller can more accurately calculate the optimal control quantity at the next moment,significantly improving the performance of distributed model predictive control(DMPC).A comparison demonstrates that the proposed adaptive sampling DMPC algorithm has better tracking performance than the traditional DMPC algorithm.
基金supported by the National Key Research and Development Program of China(No.2018YFA0703300)the National Natural Science Foundation of China(Nos.51835006,51675220 and 51875244)+5 种基金the Pre-research Joint Foundation of Equipment Development Department and Ministry of Education(No.6141A02022131)the JLU Science and Technology Innovative Research Team(No.2017TD-04)the Joint Construction Project of Jilin University and Jilin Province(No.SF2017-3-4)the Natural Science Foundation of Jilin Province of China(No.20170101115JC)the Science and technology research project of education department of Jilin province(No.20190141)the Opening Project of the Key Laboratory of Bionic Enginccring(Ministry of Education),Jilin University(No.KF20200002).
文摘Solid particle erosion on the material surfaces is a very common phenomenon in the industrial field,which greatly affects the efficiency,service life,and even poses a great threat to life safety.However,current research on erosion resistance is not only inefficient,but also limited to the improvement of hardness and toughness of materials.Inspired by typical scorpion(Parabuthus transvaalicus),biomimetic functional samples with exquisite anti-rosion structures were manufactured.Macroscopic morphology and structure of the biological prototype were analyzed and measured.According to above analysis,combined with response surface methodology,a set of biomimetic samples with different structural parameters were fabricated by using 3D printing technology.The anti-crosion performance of these biomimetic samples was investigated using a blasting jet machine.Based on the results of blasting jet test,as well as regression analysis and fiting,the optimal structural parameters were obtained.In addition to the static test conditions,the optimal biomimetic sample was also eroded in rotating condition and showed excellent erosion resistance property.The presence of bump and groove structures,on the one hand,reduced the croded area of biominetic sample surface.On the other hand,they made the airlow turbulent and consequently reduced the impact cnergy of solid particles,which significantly improved the erosion resistance of biomimetic materials.This study provides a new strategy to improvethe service life of components easily affected by erosion in the aviation,energy and military fields.
基金supported by the Hunan Provincial Natural Science Foundation of China(Nos.2025JJ70018 and 2025JJ70057)the Hunan Provincial Key Research and Development Program(No.2024JK2065).
文摘The precise and timely extraction of railway signals is crucial for the creation of railway electronic maps.This paper introduces a novel real-time detection approach for dynamically adjusting railway signals,leveraging an enhanced Real-Time DEtection TRansformer(RT-DETR)model.The enhancement involves the integration of a vision Transformer with Dynamically Quantifiable Sampling Attention Mechanism(DQSAM)into the ResNet50 backbone of the RT-DETR framework,thereby enhancing the model’s efficiency and accuracy in handling intricate visual tasks.Secondly,an ultra-lightweight and effective Dynamic Grouping upSampler(DyGSample)is inserted into the efficient hybrid encode module as the up-sampling part.This operator can effectively upsample the feature graph without increasing the computational burden,and improve the model resolution and detail capture ability.In addition,in order to solve the problem of deep layer of model network and high operating cost,a new bounding box similarity loss function of rotation intersection over union based on minimum point distance is adopted in this paper,which takes into account all relevant factors of existing loss functions,namely overlapping or non-overlapping regions,center point distance,width and height deviation,and simplifies the calculation process.As a lightweight signal detection model with ultra-fast,high real-time,and high precision,the detection accuracy of this method is improved from 90.21%to 97.45%,which proves the superior performance and effectiveness of the improved real-time dynamic adjustment RT-DETR model in railway signal extraction.
