To fully leverage the advantages of mechanization and informatization in tunnel boring machine(TBM)operations,the authors aim to promote the advancement of tunnel construction technology toward intelligent development...To fully leverage the advantages of mechanization and informatization in tunnel boring machine(TBM)operations,the authors aim to promote the advancement of tunnel construction technology toward intelligent development.This involved exploring the deep integration of next-generation artificial intelligence technologies,such as sensing technology,automatic control technology,big data technology,deep learning,and machine vision,with key operational processes,including TBM excavation,direction adjustment,step changes,inverted arch block assembly,material transportation,and operation status assurance.The results of this integration are summarized as follows.(1)TBM key excavation parameter prediction algorithm was developed with an accuracy rate exceeding 90%.The TBM intelligent step-change control algorithm,based on machine vision,achieved an image segmentation accuracy rate of 95%and gripper shoe positioning error of±5 mm.(2)An automatic positioning system for inverted arch blocks was developed,enabling real-time perception of the spatial position and deviation during the assembly process.The system maintains an elevation positioning deviation within±3 mm and a horizontal positioning deviation within±10 mm,reducing the number of surveyors in each work team.(3)A TBM intelligent rail transportation system that achieves real-time human-machine positioning,automatic switch opening and closing,automatic obstacle avoidance,intelligent transportation planning,and integrated scheduling and command was designed.Each locomotive formation reduces one shunter and improves comprehensive transportation efficiency by more than 20%.(4)Intelligent analysis and prediction algorithms were developed to monitor and predict the trends of the hydraulic and gear oil parameters in real time,enhancing the proactive maintenance and system reliability.展开更多
[Objective]Under the combined impact of climate change and urbanization,urban rainstorm flood disasters occur frequently,seriously restricting urban safety and sustainable development.Relying on traditional grey infra...[Objective]Under the combined impact of climate change and urbanization,urban rainstorm flood disasters occur frequently,seriously restricting urban safety and sustainable development.Relying on traditional grey infrastructure such as pipe networks for urban stormwater management is not enough to deal with urban rainstorm flood disasters under extreme rainfall events.The integration of green,grey and blue systems(GGB-integrated system)is gradually gaining recognition in the field of global flood prevention.It is necessary to further clarify the connotation,technical and engineering implementation strategies of the GGB-integrated system,to provide support for the resilient city construction.[Methods]Through literature retrieval and analysis,the relevant research and progress related to the layout optimization and joint scheduling optimization of the GGBintegrated system were systematically reviewed.In response to existing limitations and future engineering application requirements,key supporting technologies including the utilization of overground emergency storage spaces,safety protection of underground important infrastructure and multi-departmental collaboration,were proposed.A layout optimization framework and a joint scheduling framework for the GGB-integrated system were also developed.[Results]Current research on layout optimization predominantly focuses on the integration of green system and grey system,with relatively fewer studies incorporating blue system infrastructure into the optimization process.Moreover,these studies tend to be on a smaller scale with simpler scenarios,which do not fully capture the complexity of real-world systems.Additionally,optimization objective tend to prioritize environmental and economic goals,while social and ecological factors are less frequently considered.Current research on joint scheduling optimization is often limited to small-scale plots,with insufficient attention paid to the entire system.There is a deficiency in method for real-time,automated determination of optimal control strategies for combinations of multiple system facilities based on actual rainfall-runoff processes.Additionally,the application of emergency facilities during extreme conditions is not sufficiently addressed.Furthermore,both layout optimization and joint scheduling optimization lack consideration of the mute feed effect of flood and waterlogging in urban,watershed and regional scales.[Conclusion]Future research needs to improve the theoretical framework for layout optimization and joint scheduling optimization of GGB-integrated system.Through the comprehensive application of the Internet of things,artificial intelligence,coupling model development,multi-scale analysis,multi-scenario simulation,and the establishment of multi-departmental collaboration mechanisms,it can enhance the flood resilience of urban areas in response to rainfall events of varying intensities,particularly extreme rainfall events.展开更多
The Infrared Hyperspectral Atmospheric SounderⅡ(HIRAS-Ⅱ)is the key equipment on FengYun-3E(FY-3E)satellite,which can realize vertical atmospheric detection,featuring hyper spectral,high sensitivity and high precisio...The Infrared Hyperspectral Atmospheric SounderⅡ(HIRAS-Ⅱ)is the key equipment on FengYun-3E(FY-3E)satellite,which can realize vertical atmospheric detection,featuring hyper spectral,high sensitivity and high precision.To ensure its accuracy of detection,it is necessary to correlate their thermal models to in-orbit da⁃ta.In this work,an investigation of intelligent correlation method named Intelligent Correlation Platform for Ther⁃mal Model(ICP-TM)was established,the advanced Kriging surrogate model and efficient adaptive region opti⁃mization algorithm were introduced.After the correlation with this method for FY-3E/HIRAS-Ⅱ,the results indi⁃cate that compared with the data in orbit,the error of the thermal model has decreased from 5 K to within±1 K in cold case(10℃).Then,the correlated model is validated in hot case(20℃),and the correlated model exhibits good universality.This correlation precision is also much superiors to the general ones like 3 K in other similar lit⁃erature.Furthermore,the process is finished in 8 days using ICP-TM,the efficiency is much better than 3 months based on manual.The results show that the proposed approach significantly enhances the accuracy and efficiency of thermal model,this contributes to the precise thermal control of subsequent infrared optical payloads.展开更多
The simultaneous transmitting and reflecting reconfigurable intelligent surface(STAR-RIS)can independently adjust surface’s reflection and transmission coefficients so as to enhance space coverage.For a multiple-inpu...The simultaneous transmitting and reflecting reconfigurable intelligent surface(STAR-RIS)can independently adjust surface’s reflection and transmission coefficients so as to enhance space coverage.For a multiple-input multiple-output(MIMO)communication system with a STAR-RIS,a base station(BS),an eavesdropper,and multiple users,the system security rate is studied.A joint design of the power allocation at the transmitter and phase shift matrices for reflection and transmission at the STAR-RIS is conducted,in order to maximize the worst achievable security data rate(ASDR).Since the problem is nonconvex and hence challenging,a particle swarm optimization(PSO)based algorithm is developed to tackle the problem.Both the cases of continuous and discrete phase shift matrices at the STAR-RIS are considered.Simulation results demonstrate the effectiveness of the proposed algorithm and shows the benefits of using STAR-RIS in MIMO mutliuser systems.展开更多
Performance-based warranties(PBWs)are widely used in industry and manufacturing.Given that PBW can impose financial burdens on manufacturers,rational maintenance decisions are essential for expanding profit margins.Th...Performance-based warranties(PBWs)are widely used in industry and manufacturing.Given that PBW can impose financial burdens on manufacturers,rational maintenance decisions are essential for expanding profit margins.This paper proposes an optimization model for PBW decisions for systems affected by Gamma degradation processes,incorporating periodic inspection.A system performance degradation model is established.Preventive maintenance probability and corrective renewal probability models are developed to calculate expected warranty costs and system availability.A benefits function,which includes incentives,is constructed to optimize the initial and subsequent inspection intervals and preventive maintenance thresholds,thereby maximizing warranty profit.An improved sparrow search algorithm is developed to optimize the model,with a case study on large steam turbine rotor shafts.The results suggest the optimal PBW strategy involves an initial inspection interval of approximately 20 months,with subsequent intervals of about four months,and a preventive maintenance threshold of approximately 37.39 mm wear.When compared to common cost-minimization-based condition maintenance strategies and PBW strategies that do not differentiate between initial and subsequent inspection intervals,the proposed PBW strategy increases the manufacturer’s profit by 1%and 18%,respectively.Sensitivity analyses provide managerial recommendations for PBW implementation.The PBW strategy proposed in this study significantly increases manufacturers’profits by optimizing inspection intervals and preventive maintenance thresholds,and manufacturers should focus on technological improvement in preventive maintenance and cost control to further enhance earnings.展开更多
Shaanxi Electric Power（monthly issue）is a science and technology journal which is administrated by State Grid Corporation of China,sponsored by Shaanxi Electric Power Corporation.The journal mainly reflects the new ...Shaanxi Electric Power（monthly issue）is a science and technology journal which is administrated by State Grid Corporation of China,sponsored by Shaanxi Electric Power Corporation.The journal mainly reflects the new achievement,new technology,new trend in the fields ofdomestic＆international energy,electric technology.The scopeofShaanxi Electric Power covers new energy and distributed power generation,展开更多
Based on rational behavior model of three layers, a tracking control system is designed for straight line tracking which is commonly used in underwater survey missions. An intelligent PID control law implemented as pl...Based on rational behavior model of three layers, a tracking control system is designed for straight line tracking which is commonly used in underwater survey missions. An intelligent PID control law implemented as planning level during the control system using transverse deviation is came up with. Continuous tracking of path expressed by a point sequence can be realized by the law. Firstly, a path tracking control system based on rational behavior model of three layers is designed, mainly satisfying the needs of underactuated AUV. Since there is no need to perform spatially coupled maneuvers, the 3D path tracking control is decoupled into planar 2D path tracking and depth or height tracking separately. Secondly, planar path tracking controller is introduced. For the reason that more attention is paid to comparing with vertical position control, transverse deviation in analytical form is derived. According to the Lyapunov direct theory, control law is designed using discrete PID algorithm whose parameters obey adaptive fuzzy adjustment. Reference heading angle is given as an output of the guidance controller conducted by lateral deviation together with its derivative. For the purpose of improving control quality and facilitating parameter modifying, data normalize modules based on Sigmoid function are applied to input-output data manipulation. Lastly, a sequence of experiments was carried out successfully, including tests in Longfeng lake and at the Yellow sea. In most challenging sea conditions, tracking errors of straight line are below 2 m in general. The results show that AUV is able to compensate the disturbance brought by sea current. The provided test results demonstrate that the designed guidance controller guarantees stably and accurately straight route tracking. Besides, the proposed control system is accessible for continuous comb-shaped path tracking in region searching.展开更多
The effect of the information delay, which was caused by thc naturc of the distance sensors and wireless communication systems, on the string stability of platoon of automated vehicles was studied. The longitudinal ve...The effect of the information delay, which was caused by thc naturc of the distance sensors and wireless communication systems, on the string stability of platoon of automated vehicles was studied. The longitudinal vehicle dynamics model was built by taking the information delay into consideration, and three typical information frameworks, i.e., leader-predecessor framework （LPF）, multiple-predecessors framework （MPF） and predecessor-successor framework （PSF）, were defined and their related spacing error dynamics models in frequency domain were proposed. The string stability of platoon of automated vehicles was analyzed for the LPF, MPF and PSF, respectively. Meanwhile, the related sufficient string stable conditions were also obtained. The results demonstrate that the string stability can be guaranteed tbr the LPF and PSF with considering the information delay, but the ranges of the control gains of the control laws are smaller than those without considering the information delay. For the MPF, the ＂weak＂ string stability, which can be guaranteed without considering the information delay, cannot be obtained with considering the information delay. The comparative simulations further demonstrate that the LPF shows better string stability, but the PSF shows better string scalable performance.展开更多
During the compaction of a road subgrade, the mechanical parameters of the soil mass change in real time, but current research assumes that these parameters remain unchanged. In order to address this discrepancy, this...During the compaction of a road subgrade, the mechanical parameters of the soil mass change in real time, but current research assumes that these parameters remain unchanged. In order to address this discrepancy, this paper establishes a relationship between the degree of compaction K and strain ε. The relationship between the compaction degree K and the shear strength of soil(cohesion c and frictional angle φ) was clearly established through indoor experiments. The subroutine UMAT in ABAQUS finite element numerical software was developed to realize an accurate calculation of the subgrade soil compaction quality. This value was compared and analyzed against the assumed compaction value of the model, thereby verifying the accuracy of the intelligent compaction calculation results for subgrade soil. On this basis, orthogonal tests of the influential factors(frequency, amplitude, and quality) for the degree of compaction and sensitivity analysis were carried out. Finally, the ‘acceleration intelligent compaction value’, which is based on the acceleration signal, is proposed for a compaction meter value that indicates poor accuracy. The research results can provide guidance and basis for further research into the accurate control of compaction quality for roadbeds and pavements.展开更多
To realize the requirement of diagnostic sequence optimization in the process of design for testability, the authors put forward an optimization method based on quantum-behaved particle swarm optimization （QPSO） alg...To realize the requirement of diagnostic sequence optimization in the process of design for testability, the authors put forward an optimization method based on quantum-behaved particle swarm optimization （QPSO） algorithm. By a precedence ordering coding, the diagnostic sequence optimization can be translated into a precedence ordering problem in the multidimensional space of swarm. It can get the optimizing order quickly by using the powerful and quick search capability of QPSO algorithm, and the order is the diagnostic sequence for the system. The realization of the method is simpler than other methods, and the results are more excellent than others, and it has been applied in the engineering practice.展开更多
The FMS (Flexible Manufacture System)Research Group in the Mechanical Engineering Department has recently developed an intelligent strategy based on artificial intelligence and practical experiences for the defection ...The FMS (Flexible Manufacture System)Research Group in the Mechanical Engineering Department has recently developed an intelligent strategy based on artificial intelligence and practical experiences for the defection of tool failure (wear or fracture or breakage).展开更多
The connected and automated vehicles(CAVs)technologies provide more information to drivers in the car-following(CF)process.Unlike the human-driven vehicles(HVs),which only considers information in front,the CAVs circu...The connected and automated vehicles(CAVs)technologies provide more information to drivers in the car-following(CF)process.Unlike the human-driven vehicles(HVs),which only considers information in front,the CAVs circumstance allows them to obtain information in front and behind,enhancing vehicles perception ability.This paper proposes an intelligent back-looking distance driver model(IBDM)considering the desired distance of the following vehicle in homogeneous CAVs environment.Based on intelligent driver model(IDM),the IBDM integrates behind information of vehicles as a control term.The stability condition against a small perturbation is analyzed using linear stability theory in the homogeneous traffic flow.To validate the theoretical analysis,simulations are carried out on a single lane under the open boundary condition,and compared with the IDM not considering the following vehicle and the extended IDM considering the information of vehicle preceding and next preceding.Six scenarios are designed to evaluate the results under different disturbance strength,disturbance location,and initial platoon space distance.The results reveal that the IBDM has an advantage over IDM and the extended IDM in control of CAVs car-following process in maintaining string stability,and the stability improves by increasing the proportion of the new item.展开更多
Short-term traffic flow forecasting is a significant part of intelligent transportation system.In some traffic control scenarios,obtaining future traffic flow in advance is conducive to highway management department t...Short-term traffic flow forecasting is a significant part of intelligent transportation system.In some traffic control scenarios,obtaining future traffic flow in advance is conducive to highway management department to have sufficient time to formulate corresponding traffic flow control measures.In hence,it is meaningful to establish an accurate short-term traffic flow method and provide reference for peak traffic flow warning.This paper proposed a new hybrid model for traffic flow forecasting,which is composed of the variational mode decomposition(VMD)method,the group method of data handling(GMDH)neural network,bi-directional long and short term memory(BILSTM)network and ELMAN network,and is optimized by the imperialist competitive algorithm(ICA)method.To illustrate the performance of the proposed model,there are several comparative experiments between the proposed model and other models.The experiment results show that 1)BILSTM network,GMDH network and ELMAN network have better predictive performance than other single models;2)VMD can significantly improve the predictive performance of the ICA-GMDH-BILSTM-ELMAN model.The effect of VMD method is better than that of EEMD method and FEEMD method.To conclude,the proposed model which is made up of the VMD method,the ICA method,the BILSTM network,the GMDH network and the ELMAN network has excellent predictive ability for traffic flow series.展开更多
Modern agricultural mechanization has put forward higher requirements for the intelligent defect diagnosis.However,the fault features are usually learned and classified under all speeds without considering the effects...Modern agricultural mechanization has put forward higher requirements for the intelligent defect diagnosis.However,the fault features are usually learned and classified under all speeds without considering the effects of speed fluctuation.To overcome this deficiency,a novel intelligent defect detection framework based on time-frequency transformation is presented in this work.In the framework,the samples under one speed are employed for training sparse filtering model,and the remaining samples under different speeds are adopted for testing the effectiveness.Our proposed approach contains two stages:1)the time-frequency domain signals are acquired from the mechanical raw vibration data by the short time Fourier transform algorithm,and then the defect features are extracted from time-frequency domain signals by sparse filtering algorithm;2)different defect types are classified by the softmax regression using the defect features.The proposed approach can be employed to mine available fault characteristics adaptively and is an effective intelligent method for fault detection of agricultural equipment.The fault detection performances confirm that our approach not only owns strong ability for fault classification under different speeds,but also obtains higher identification accuracy than the other methods.展开更多
Driving safety field(DSF) model has been proposed to represent comprehensive driving risk formed by interactions of driver-vehicle-road in mixed traffic environment. In this work, we establish an optimization model ba...Driving safety field(DSF) model has been proposed to represent comprehensive driving risk formed by interactions of driver-vehicle-road in mixed traffic environment. In this work, we establish an optimization model based on grey relation degree analysis to calibrate risk coefficients of DSF model. To solve the optimum solution, a genetic algorithm is employed. Finally, the DSF model is verified through a real-world driving experiment. Results show that the DSF model is consistent with driver's hazard perception and more sensitive than TTC. Moreover, the proposed DSF model offers a novel way for criticality assessment and decision-making of advanced driver assistance systems and intelligent connected vehicles.展开更多
文摘To fully leverage the advantages of mechanization and informatization in tunnel boring machine(TBM)operations,the authors aim to promote the advancement of tunnel construction technology toward intelligent development.This involved exploring the deep integration of next-generation artificial intelligence technologies,such as sensing technology,automatic control technology,big data technology,deep learning,and machine vision,with key operational processes,including TBM excavation,direction adjustment,step changes,inverted arch block assembly,material transportation,and operation status assurance.The results of this integration are summarized as follows.(1)TBM key excavation parameter prediction algorithm was developed with an accuracy rate exceeding 90%.The TBM intelligent step-change control algorithm,based on machine vision,achieved an image segmentation accuracy rate of 95%and gripper shoe positioning error of±5 mm.(2)An automatic positioning system for inverted arch blocks was developed,enabling real-time perception of the spatial position and deviation during the assembly process.The system maintains an elevation positioning deviation within±3 mm and a horizontal positioning deviation within±10 mm,reducing the number of surveyors in each work team.(3)A TBM intelligent rail transportation system that achieves real-time human-machine positioning,automatic switch opening and closing,automatic obstacle avoidance,intelligent transportation planning,and integrated scheduling and command was designed.Each locomotive formation reduces one shunter and improves comprehensive transportation efficiency by more than 20%.(4)Intelligent analysis and prediction algorithms were developed to monitor and predict the trends of the hydraulic and gear oil parameters in real time,enhancing the proactive maintenance and system reliability.
文摘[Objective]Under the combined impact of climate change and urbanization,urban rainstorm flood disasters occur frequently,seriously restricting urban safety and sustainable development.Relying on traditional grey infrastructure such as pipe networks for urban stormwater management is not enough to deal with urban rainstorm flood disasters under extreme rainfall events.The integration of green,grey and blue systems(GGB-integrated system)is gradually gaining recognition in the field of global flood prevention.It is necessary to further clarify the connotation,technical and engineering implementation strategies of the GGB-integrated system,to provide support for the resilient city construction.[Methods]Through literature retrieval and analysis,the relevant research and progress related to the layout optimization and joint scheduling optimization of the GGBintegrated system were systematically reviewed.In response to existing limitations and future engineering application requirements,key supporting technologies including the utilization of overground emergency storage spaces,safety protection of underground important infrastructure and multi-departmental collaboration,were proposed.A layout optimization framework and a joint scheduling framework for the GGB-integrated system were also developed.[Results]Current research on layout optimization predominantly focuses on the integration of green system and grey system,with relatively fewer studies incorporating blue system infrastructure into the optimization process.Moreover,these studies tend to be on a smaller scale with simpler scenarios,which do not fully capture the complexity of real-world systems.Additionally,optimization objective tend to prioritize environmental and economic goals,while social and ecological factors are less frequently considered.Current research on joint scheduling optimization is often limited to small-scale plots,with insufficient attention paid to the entire system.There is a deficiency in method for real-time,automated determination of optimal control strategies for combinations of multiple system facilities based on actual rainfall-runoff processes.Additionally,the application of emergency facilities during extreme conditions is not sufficiently addressed.Furthermore,both layout optimization and joint scheduling optimization lack consideration of the mute feed effect of flood and waterlogging in urban,watershed and regional scales.[Conclusion]Future research needs to improve the theoretical framework for layout optimization and joint scheduling optimization of GGB-integrated system.Through the comprehensive application of the Internet of things,artificial intelligence,coupling model development,multi-scale analysis,multi-scenario simulation,and the establishment of multi-departmental collaboration mechanisms,it can enhance the flood resilience of urban areas in response to rainfall events of varying intensities,particularly extreme rainfall events.
基金Supported by the National Key Research and Development Program of China(2022YFB3904803)。
文摘The Infrared Hyperspectral Atmospheric SounderⅡ(HIRAS-Ⅱ)is the key equipment on FengYun-3E(FY-3E)satellite,which can realize vertical atmospheric detection,featuring hyper spectral,high sensitivity and high precision.To ensure its accuracy of detection,it is necessary to correlate their thermal models to in-orbit da⁃ta.In this work,an investigation of intelligent correlation method named Intelligent Correlation Platform for Ther⁃mal Model(ICP-TM)was established,the advanced Kriging surrogate model and efficient adaptive region opti⁃mization algorithm were introduced.After the correlation with this method for FY-3E/HIRAS-Ⅱ,the results indi⁃cate that compared with the data in orbit,the error of the thermal model has decreased from 5 K to within±1 K in cold case(10℃).Then,the correlated model is validated in hot case(20℃),and the correlated model exhibits good universality.This correlation precision is also much superiors to the general ones like 3 K in other similar lit⁃erature.Furthermore,the process is finished in 8 days using ICP-TM,the efficiency is much better than 3 months based on manual.The results show that the proposed approach significantly enhances the accuracy and efficiency of thermal model,this contributes to the precise thermal control of subsequent infrared optical payloads.
文摘The simultaneous transmitting and reflecting reconfigurable intelligent surface(STAR-RIS)can independently adjust surface’s reflection and transmission coefficients so as to enhance space coverage.For a multiple-input multiple-output(MIMO)communication system with a STAR-RIS,a base station(BS),an eavesdropper,and multiple users,the system security rate is studied.A joint design of the power allocation at the transmitter and phase shift matrices for reflection and transmission at the STAR-RIS is conducted,in order to maximize the worst achievable security data rate(ASDR).Since the problem is nonconvex and hence challenging,a particle swarm optimization(PSO)based algorithm is developed to tackle the problem.Both the cases of continuous and discrete phase shift matrices at the STAR-RIS are considered.Simulation results demonstrate the effectiveness of the proposed algorithm and shows the benefits of using STAR-RIS in MIMO mutliuser systems.
基金supported by the National Natural Science Foundation of China(71871219).
文摘Performance-based warranties(PBWs)are widely used in industry and manufacturing.Given that PBW can impose financial burdens on manufacturers,rational maintenance decisions are essential for expanding profit margins.This paper proposes an optimization model for PBW decisions for systems affected by Gamma degradation processes,incorporating periodic inspection.A system performance degradation model is established.Preventive maintenance probability and corrective renewal probability models are developed to calculate expected warranty costs and system availability.A benefits function,which includes incentives,is constructed to optimize the initial and subsequent inspection intervals and preventive maintenance thresholds,thereby maximizing warranty profit.An improved sparrow search algorithm is developed to optimize the model,with a case study on large steam turbine rotor shafts.The results suggest the optimal PBW strategy involves an initial inspection interval of approximately 20 months,with subsequent intervals of about four months,and a preventive maintenance threshold of approximately 37.39 mm wear.When compared to common cost-minimization-based condition maintenance strategies and PBW strategies that do not differentiate between initial and subsequent inspection intervals,the proposed PBW strategy increases the manufacturer’s profit by 1%and 18%,respectively.Sensitivity analyses provide managerial recommendations for PBW implementation.The PBW strategy proposed in this study significantly increases manufacturers’profits by optimizing inspection intervals and preventive maintenance thresholds,and manufacturers should focus on technological improvement in preventive maintenance and cost control to further enhance earnings.
文摘软件工程自1968年提出以来,一直是提高软件开发效率、保障软件质量的有效手段.软件的发展及内涵被归纳为3个空间：平台空间、认知空间和问题空间,相应地,软件工程发展也从传统的模式化转向知识化和智能化.基于搜索的软件工程（search based software engineering,简称SBSE）是传统软件工程和智能计算（intelligent computing）交叉的新兴研究领域,从问题的解空间出发,
文摘Shaanxi Electric Power（monthly issue）is a science and technology journal which is administrated by State Grid Corporation of China,sponsored by Shaanxi Electric Power Corporation.The journal mainly reflects the new achievement,new technology,new trend in the fields ofdomestic＆international energy,electric technology.The scopeofShaanxi Electric Power covers new energy and distributed power generation,
基金Projects(51179035,51279221) supported by the National Natural Science Foundation of ChinaProject(2014M561333) supported by Postdoctoral Science Foundation of China
文摘Based on rational behavior model of three layers, a tracking control system is designed for straight line tracking which is commonly used in underwater survey missions. An intelligent PID control law implemented as planning level during the control system using transverse deviation is came up with. Continuous tracking of path expressed by a point sequence can be realized by the law. Firstly, a path tracking control system based on rational behavior model of three layers is designed, mainly satisfying the needs of underactuated AUV. Since there is no need to perform spatially coupled maneuvers, the 3D path tracking control is decoupled into planar 2D path tracking and depth or height tracking separately. Secondly, planar path tracking controller is introduced. For the reason that more attention is paid to comparing with vertical position control, transverse deviation in analytical form is derived. According to the Lyapunov direct theory, control law is designed using discrete PID algorithm whose parameters obey adaptive fuzzy adjustment. Reference heading angle is given as an output of the guidance controller conducted by lateral deviation together with its derivative. For the purpose of improving control quality and facilitating parameter modifying, data normalize modules based on Sigmoid function are applied to input-output data manipulation. Lastly, a sequence of experiments was carried out successfully, including tests in Longfeng lake and at the Yellow sea. In most challenging sea conditions, tracking errors of straight line are below 2 m in general. The results show that AUV is able to compensate the disturbance brought by sea current. The provided test results demonstrate that the designed guidance controller guarantees stably and accurately straight route tracking. Besides, the proposed control system is accessible for continuous comb-shaped path tracking in region searching.
基金Project(20070006011) supported by the Doctoral Foundation of Ministry of Education of China
文摘The effect of the information delay, which was caused by thc naturc of the distance sensors and wireless communication systems, on the string stability of platoon of automated vehicles was studied. The longitudinal vehicle dynamics model was built by taking the information delay into consideration, and three typical information frameworks, i.e., leader-predecessor framework （LPF）, multiple-predecessors framework （MPF） and predecessor-successor framework （PSF）, were defined and their related spacing error dynamics models in frequency domain were proposed. The string stability of platoon of automated vehicles was analyzed for the LPF, MPF and PSF, respectively. Meanwhile, the related sufficient string stable conditions were also obtained. The results demonstrate that the string stability can be guaranteed tbr the LPF and PSF with considering the information delay, but the ranges of the control gains of the control laws are smaller than those without considering the information delay. For the MPF, the ＂weak＂ string stability, which can be guaranteed without considering the information delay, cannot be obtained with considering the information delay. The comparative simulations further demonstrate that the LPF shows better string stability, but the PSF shows better string scalable performance.
基金Project(51878164) supported by the National Natural Science Foundation of ChinaProjects(BK20161421, BK20140109) supported by the Natural Science Foundation of Jiangsu Province, China+4 种基金Project(141076) supported by the Huoyingdong Foundation of the Ministry of Education of ChinaProject(BZ2017011) supported by the Science and Technology Support Project of Jiangsu Province, ChinaProject(2242015R30027) supported by the Fundamental Research Funds for the Central Universities, ChinaProject(grant number KFJ170106) supported by the Changsha University of Science & Technology via Open Fund of National Engineering Laboratory of Highway Maintenance Technology, ChinaProject(2018B51) supported by the Science and Technology Support Project of Qilu Transportation Development Group, China。
文摘During the compaction of a road subgrade, the mechanical parameters of the soil mass change in real time, but current research assumes that these parameters remain unchanged. In order to address this discrepancy, this paper establishes a relationship between the degree of compaction K and strain ε. The relationship between the compaction degree K and the shear strength of soil(cohesion c and frictional angle φ) was clearly established through indoor experiments. The subroutine UMAT in ABAQUS finite element numerical software was developed to realize an accurate calculation of the subgrade soil compaction quality. This value was compared and analyzed against the assumed compaction value of the model, thereby verifying the accuracy of the intelligent compaction calculation results for subgrade soil. On this basis, orthogonal tests of the influential factors(frequency, amplitude, and quality) for the degree of compaction and sensitivity analysis were carried out. Finally, the ‘acceleration intelligent compaction value’, which is based on the acceleration signal, is proposed for a compaction meter value that indicates poor accuracy. The research results can provide guidance and basis for further research into the accurate control of compaction quality for roadbeds and pavements.
基金supported by the National Natural Science Foundation of China(60771063).
文摘To realize the requirement of diagnostic sequence optimization in the process of design for testability, the authors put forward an optimization method based on quantum-behaved particle swarm optimization （QPSO） algorithm. By a precedence ordering coding, the diagnostic sequence optimization can be translated into a precedence ordering problem in the multidimensional space of swarm. It can get the optimizing order quickly by using the powerful and quick search capability of QPSO algorithm, and the order is the diagnostic sequence for the system. The realization of the method is simpler than other methods, and the results are more excellent than others, and it has been applied in the engineering practice.
文摘The FMS (Flexible Manufacture System)Research Group in the Mechanical Engineering Department has recently developed an intelligent strategy based on artificial intelligence and practical experiences for the defection of tool failure (wear or fracture or breakage).
基金Project(2018YFB1600600)supported by the National Key Research and Development Program,ChinaProject(20YJAZH083)supported by the Ministry of Education,China+1 种基金Project(20YJAZH083)supported by the Humanities and Social Sciences,ChinaProject(51878161)supported by the National Natural Science Foundation of China。
文摘The connected and automated vehicles(CAVs)technologies provide more information to drivers in the car-following(CF)process.Unlike the human-driven vehicles(HVs),which only considers information in front,the CAVs circumstance allows them to obtain information in front and behind,enhancing vehicles perception ability.This paper proposes an intelligent back-looking distance driver model(IBDM)considering the desired distance of the following vehicle in homogeneous CAVs environment.Based on intelligent driver model(IDM),the IBDM integrates behind information of vehicles as a control term.The stability condition against a small perturbation is analyzed using linear stability theory in the homogeneous traffic flow.To validate the theoretical analysis,simulations are carried out on a single lane under the open boundary condition,and compared with the IDM not considering the following vehicle and the extended IDM considering the information of vehicle preceding and next preceding.Six scenarios are designed to evaluate the results under different disturbance strength,disturbance location,and initial platoon space distance.The results reveal that the IBDM has an advantage over IDM and the extended IDM in control of CAVs car-following process in maintaining string stability,and the stability improves by increasing the proportion of the new item.
基金Project(61873283)supported by the National Natural Science Foundation of ChinaProject(KQ1707017)supported by the Changsha Science&Technology Project,ChinaProject(2019CX005)supported by the Innovation Driven Project of the Central South University,China。
文摘Short-term traffic flow forecasting is a significant part of intelligent transportation system.In some traffic control scenarios,obtaining future traffic flow in advance is conducive to highway management department to have sufficient time to formulate corresponding traffic flow control measures.In hence,it is meaningful to establish an accurate short-term traffic flow method and provide reference for peak traffic flow warning.This paper proposed a new hybrid model for traffic flow forecasting,which is composed of the variational mode decomposition(VMD)method,the group method of data handling(GMDH)neural network,bi-directional long and short term memory(BILSTM)network and ELMAN network,and is optimized by the imperialist competitive algorithm(ICA)method.To illustrate the performance of the proposed model,there are several comparative experiments between the proposed model and other models.The experiment results show that 1)BILSTM network,GMDH network and ELMAN network have better predictive performance than other single models;2)VMD can significantly improve the predictive performance of the ICA-GMDH-BILSTM-ELMAN model.The effect of VMD method is better than that of EEMD method and FEEMD method.To conclude,the proposed model which is made up of the VMD method,the ICA method,the BILSTM network,the GMDH network and the ELMAN network has excellent predictive ability for traffic flow series.
基金Project(51675262)supported by the National Natural Science Foundation of ChinaProject(2016YFD0700800)supported by the National Key Research and Development Program of China+2 种基金Project(6140210020102)supported by the Advance Research Field Fund Project of ChinaProject(NP2018304)supported by the Fundamental Research Funds for the Central Universities,ChinaProject(2017-IV-0008-0045)supported by the National Science and Technology Major Project
文摘Modern agricultural mechanization has put forward higher requirements for the intelligent defect diagnosis.However,the fault features are usually learned and classified under all speeds without considering the effects of speed fluctuation.To overcome this deficiency,a novel intelligent defect detection framework based on time-frequency transformation is presented in this work.In the framework,the samples under one speed are employed for training sparse filtering model,and the remaining samples under different speeds are adopted for testing the effectiveness.Our proposed approach contains two stages:1)the time-frequency domain signals are acquired from the mechanical raw vibration data by the short time Fourier transform algorithm,and then the defect features are extracted from time-frequency domain signals by sparse filtering algorithm;2)different defect types are classified by the softmax regression using the defect features.The proposed approach can be employed to mine available fault characteristics adaptively and is an effective intelligent method for fault detection of agricultural equipment.The fault detection performances confirm that our approach not only owns strong ability for fault classification under different speeds,but also obtains higher identification accuracy than the other methods.
基金Projects(51475254,51625503)supported by the National Natural Science Foundation of ChinaProject(MCM20150302)supported by the Joint Project of Tsinghua and China Mobile,ChinaProject supported by the joint Project of Tsinghua and Daimler Greater China Ltd.,Beijing,China
文摘Driving safety field(DSF) model has been proposed to represent comprehensive driving risk formed by interactions of driver-vehicle-road in mixed traffic environment. In this work, we establish an optimization model based on grey relation degree analysis to calibrate risk coefficients of DSF model. To solve the optimum solution, a genetic algorithm is employed. Finally, the DSF model is verified through a real-world driving experiment. Results show that the DSF model is consistent with driver's hazard perception and more sensitive than TTC. Moreover, the proposed DSF model offers a novel way for criticality assessment and decision-making of advanced driver assistance systems and intelligent connected vehicles.
