To effectively estimate the unknown aerodynamic parameters from the aircraft’s flight data,this paper proposes a novel aerodynamic parameter estimation method incorporating a stacked Long Short-Term Memory(LSTM)netwo...To effectively estimate the unknown aerodynamic parameters from the aircraft’s flight data,this paper proposes a novel aerodynamic parameter estimation method incorporating a stacked Long Short-Term Memory(LSTM)network model and the Levenberg-Marquardt(LM)method.The stacked LSTM network model was designed to realize the aircraft dynamics modeling by utilizing a frame of nonlinear functional mapping based entirely on the measured input-output data of the aircraft system without requiring explicit postulation of the dynamics.The LM method combines the already-trained LSTM network model to optimize the unknown aerodynamic parameters.The proposed method is applied by using the real flight data,generated by ATTAS aircraft and a bio-inspired morphing Unmanned Aerial Vehicle(UAV).The investigation reveals that for the two different flight data,the designed stacked LSTM network structure can maintain the efficacy of the network prediction capability only by appropriately adjusting the dropout rates of its hidden layers without changing other network parameters(i.e.,the initial weights,initial biases,number of hidden cells,time-steps,learning rate,and number of training iterations).Besides,the proposed method’s effectiveness and potential are demonstrated by comparing the estimated results of the ATTAS aircraft or the bio-inspired morphing UAV with the corresponding reference values or wind-tunnel results.展开更多
The simulation precision of the classic load model(CLM)is affected by the increasing proportion of installed energy storage capacity in the grid.This paper studies the all-vanadium redox flow battery(VRB)and proposes ...The simulation precision of the classic load model(CLM)is affected by the increasing proportion of installed energy storage capacity in the grid.This paper studies the all-vanadium redox flow battery(VRB)and proposes an equivalent model based on the measurement-based load modeling method,which can simulate the maximum output of the VRB energy storage system and fit the external characteristic of the system precisely in the occurrence of large disturbance and continuous small disturbance.The equivalent model is connected to CLM to form a generalized synthesis load model(GSLM),which considers the parameters of distribution network and reactive power compensation.Compared with CLM,GSLM has better structures and can describe the load characteristics of distribution network with energy storage system more precisely.Simulation results validate the effectiveness and good parameter stability of GSLM,and show that the higher the proportion of energy storage in the grid is the better description ability GSLM has.展开更多
Xigeda formation is a type of hundredmeter-thick lacustrine sediments of being prone to triggering landslides along the trunk channel and tributaries of the upper Yangtze River in China. The Yonglang landslide located...Xigeda formation is a type of hundredmeter-thick lacustrine sediments of being prone to triggering landslides along the trunk channel and tributaries of the upper Yangtze River in China. The Yonglang landslide located near Yonglang Town of Dechang County in Sichuan Province of China, which was a typical Xigeda formation landslide, was stabilized by anti-slide piles. Loading tests on a loading-test pile were conducted to measure the displacements and moments. The uncertainty of the tested geomechanical parameters of the Yonglang landslide over certain ranges would be problematic during the evaluation of the landslide. Thus, uniform design was introduced in the experimental design,and by which, numerical analyses of the loading-test pile were performed using Fast Lagrangian Analysis of Continua(FLAC3D) to acquire a database of the geomechanical parameters of the Yonglang landslide and the corresponding displacements of the loadingtest pile. A three-layer back-propagation neural network was established and trained with the database, and then tested and verified for its accuracy and reliability in numerical simulations. Displacement back analysis was conducted by substituting the displacements of the loading-test pile to the well-trained three-layer back-propagation neural network so as to identify the geomechanical parameters of the Yonglang landslide. The neuralnetwork-based displacement back analysis method with the proposed methodology is verified to be accurate and reliable for the identification of the uncertain geomechanical parameters of landslides.展开更多
Superconductive properties for oxides were predicted by artificial neural network (ANN) method with structural and chemical parameters as inputs. The predicted properties include superconductivity for oxides, distribu...Superconductive properties for oxides were predicted by artificial neural network (ANN) method with structural and chemical parameters as inputs. The predicted properties include superconductivity for oxides, distributed ranges of the superconductive transition temperature (Tc) for complex oxides, and Tc values for cuprate superconductors. The calculated results indicated that the adjusted ANN can be used to predict superconductive properties for unknown oxides.展开更多
The multi- layers feedforward neural network is used for inversion ofmaterial constants of fluid-saturated porous media. The direct analysis of fluid-saturated porousmedia is carried out with the boundary element meth...The multi- layers feedforward neural network is used for inversion ofmaterial constants of fluid-saturated porous media. The direct analysis of fluid-saturated porousmedia is carried out with the boundary element method. The dynamic displacement responses obtainedfrom direct analysis for prescribed material parameters constitute the sample sets training neuralnetwork. By virtue of the effective L-M training algorithm and the Tikhonov regularization method aswell as the GCV method for an appropriate selection of regu-larization parameter, the inversemapping from dynamic displacement responses to material constants is performed. Numerical examplesdemonstrate the validity of the neural network method.展开更多
A complete study for the implementation of wireless sensor networks in the intelligent building is presented. We carry out some experiments to find out the factors affecting the network performance. Several vital para...A complete study for the implementation of wireless sensor networks in the intelligent building is presented. We carry out some experiments to find out the factors affecting the network performance. Several vital parameters which are related to the link quality are measured before deploying the actual system. And then, we propose an optimized routing protocol based on the analysis of the test data. We evaluate the deployment strategies to ensure the excellent performance of the wireless sensor networks under the real working conditions. And the evaluation results show that the presented system could satisfy the requirements of the applications in the intelligent building.展开更多
Dune networks are widely distributed in the world＇s deserts,which include primary ridges and secondary ridges.However,they have not been sufficiently studied in a systematic manner and their origins and spatial and m...Dune networks are widely distributed in the world＇s deserts,which include primary ridges and secondary ridges.However,they have not been sufficiently studied in a systematic manner and their origins and spatial and morphological characteristics remain unclear.To provide information on the geomorphology of dune networks,we analyze the software geomorphologic patterns of the dune networks in China＇s Tengger Desert using matrix and laboratory to process remote-sensing images.Based on analysis of image features and their layout in a topographic map,we identify two types of dune networks （square and rectangular dune networks） with different size and morphological structures in the Tengger Desert.Four important geomorphic pattern parameters,ridge length,spacing,orientation and defect density,are analyzed.The length of primary ridges of dune networks decreases from northwest of the desert to the southeast,resulting an increasing spacing and a transition from rectangular dune networks to square dune networks.Wind regime and sediment supply are responsible for the variation in pattern parameters.We use the spacing and defect density data to estimate the construction time of dune networks and found that the dune networks in the Tengger Desert formed since about 1.3 ka BP.展开更多
In large mines,single fan is usually not enough to ventilate all the working areas.Single mine-fan approach cannot be directly applied to multiple-fan networks because the present of multiple pressures and air quantit...In large mines,single fan is usually not enough to ventilate all the working areas.Single mine-fan approach cannot be directly applied to multiple-fan networks because the present of multiple pressures and air quantities associated with each fan in the network.Accordingly,each fan in a multiple-fan system has its own mine characteristic curve,or a subsystem curve.Under some consideration,the conventional concept of a mine characteristic curve of a single-fan system can be directly extended to that of a particular fan within a multiple-fan system.In this paper the mutual effect of the fans on each other and their effect on the stability of the ventilation network were investigated by Hardy Cross algorithm combined with a switching-parameters technique.To show the validity and reliability of this algorithm,the stability of the ventilation system of Abu-Tartur Mine(one of the largest underground mine in Egypt)has been studied.展开更多
A sequential diagnosis method is proposed based on a fuzzy neural network realized by ＂the partially-linearized neural network （PNN）＂, by which the fault types of rotating machinery can be precisely and effectivel...A sequential diagnosis method is proposed based on a fuzzy neural network realized by ＂the partially-linearized neural network （PNN）＂, by which the fault types of rotating machinery can be precisely and effectively distinguished at an early stage on the basis of the possibilities of symptom parameters. The non-dimensional symptom parameters in time domain are defined for reflecting the features of time signals measured for the fault diagnosis of rotating machinery. The synthetic detection index is also proposed to evaluate the sensitivity of non-dimensional symptom parameters for detecting faults. The practical example of condition diagnosis for detecting and distinguishing fault states of a centrifugal pump system, such as cavitation, impeller eccentricity which often occur in a centrifugal pump system, are shown to verify the efficiency of the method proposed in this paper.展开更多
This study is focused on the discussion of a modern GNSS network and datum in Uzbekistan. Considering the significance difference （up to 200 m） in positions of the local ellipsoidal datum and the global datum, the p...This study is focused on the discussion of a modern GNSS network and datum in Uzbekistan. Considering the significance difference （up to 200 m） in positions of the local ellipsoidal datum and the global datum, the precise transformation parameters between national geodetic datum CS-42, and the World Geodetic System 1984 （WGS84） global datum used by the GPS is estimated. This study aims to evaluate the ac- curacy of the currently used transformation parameters from different sources in the region, and give preliminary recommendations for using these sets also. The differences between transformed, original and WGS-84 coordinates were calculated and evaluated. On the basis of this difference, different zones for determination of transformation parameters have been proposed.This study is focused on the discussion of a modern GNSS network and datum in Uzbekistan. Considering the significance difference （up to 200 m） in positions of the local ellipsoidal datum and the global datum, the precise transformation parameters between national geodetic datum CS-42, and the World Geodetic System 1984 （WGS84） global datum used by the GPS is estimated. This study aims to evaluate the accuracy of the currently used transformation parameters from different sources in the region, and give preliminary recommendations for using these sets also. The differences between transformed, original and WGS-84 coordinates were calculated and evaluated. On the basis of this difference, different zones for determination of transformation parameters have been proposed.展开更多
The multicast routing problem with multiple QoS constraints in networks with uncertain parameters is discussed, and a network model that is suitable to research such QoS multicast routing problem is described. The QMR...The multicast routing problem with multiple QoS constraints in networks with uncertain parameters is discussed, and a network model that is suitable to research such QoS multicast routing problem is described. The QMRGA, a multicast routing policy for Internet, mobile network or other highperformance networks is mainly presented, which is based on the genetic algorithm(GA), and can provide QoSsensitive paths in a scalable and flexible way in the network environment with uncertain parameters. The QMRGA can also optimize the network resources such as bandwidth and delay, and can converge to the optimal or nearoptimal solution within few iterations, even for the network environment with uncertain parameters. The incremental rate of computational cost can be close to a polynomial and is less than exponential rate. The performance measures of the QMRGA are evaluated by using simulations. The results show that QMRGA provides an available approach to QoS multicast routing in network environment with uncertain parameters.展开更多
A new parameter coordination and robust optimization approach for multidisciplinary design is presented. Firstly, the constraints network model is established to support engineering change, coordination and optimizati...A new parameter coordination and robust optimization approach for multidisciplinary design is presented. Firstly, the constraints network model is established to support engineering change, coordination and optimization. In this model, interval boxes are adopted to describe the uncertainty of design parameters quantitatively to enhance the design robustness. Secondly, the parameter coordination method is presented to solve the constraints network model, monitor the potential conflicts due to engineering changes, and obtain the consistency solution space corresponding to the given product specifications. Finally, the robust parameter optimization model is established, and genetic arithmetic is used to obtain the robust optimization parameter. An example of bogie design is analyzed to show the scheme to be effective.展开更多
In this paper, multimodel and neural emulators are proposed for uncoupled multivariable nonlinear plants with unknown dynamics. The contributions of this paper are to extend the emulators to multivariable non square s...In this paper, multimodel and neural emulators are proposed for uncoupled multivariable nonlinear plants with unknown dynamics. The contributions of this paper are to extend the emulators to multivariable non square systems and to propose a systematic method to compute the multimodel synthesis parameters. The effectiveness of the proposed emulators is shown through two simulation examples. The obtained results are very satisfactory, they illustrate the performance of both emulators and show the advantages of the multimodel emulator relatively to the neural one.展开更多
Heat and thermal problems are major obstacles to achieving high power density in compact permanent magnet(PM)topologies.Consequently,a comprehensive,accurate,and rapid temperature rise estimation method is required fo...Heat and thermal problems are major obstacles to achieving high power density in compact permanent magnet(PM)topologies.Consequently,a comprehensive,accurate,and rapid temperature rise estimation method is required for novel electric machines to ensure safe and reliable operations.A unique three-dimensional(3D)lumped parameter thermal network(LPTN)is presented for accurate thermal modeling of a newly developed outer-rotor hybrid-PM flux switching generator(OR-HPMFSG)for direct-drive applications.First,the losses of the OR-HPMFSG are calculated using 3D finite element analysis(FEA).Subsequently,all machine components considering the thermal contact resistance,anisotropic thermal conductivity of materials,and various heat flow paths are comprehensively modeled based on the thermal resistances.In the proposed 3-D LPTN,internal nodes are considered to predict the average temperature as well as the hot spots of all active and passive components.Experimental measurements are performed on a prototype OR-HPMFSG to validate the efficiency of the 3-D LPTN.A comparison of the results at various operating points between the developed 3-D LPTN,experimental test,and FEA indicates that the 3-D LPTN quickly approximates the hotspot and mean temperature of all components under both transient and steady states with high accuracy.展开更多
Neural activity extraction and neural decoding from neural signals are an important part of critical components of brain-computer interface systems.With the development of brain-computer interface technology,the deman...Neural activity extraction and neural decoding from neural signals are an important part of critical components of brain-computer interface systems.With the development of brain-computer interface technology,the demand for precise external control and nervous activities in macaque monkey during unilateral hand grasp has increased the complexity of control and neural decoding,which puts forward higher requirements for the accuracy and stability of feature extraction and neural decoding.In this study,a micro Capsnet network architecture that consists of a few network layers,a vector feature structure,and optimization network parameters,is proposed to decrease the computing time and complexity,decrease artificial debugging,and improve the decoding accuracy.Compared with KNN,SVM,XGBOOST,CNN,Simple RNN,and LSTM,the algorithm in this study improves the decoding accuracy by 98.03%,and achieves state-of-the-art accuracy and stronger robustness.Furthermore,the proposed algorithm can further enhance the control accuracy in the brain-computer interface.展开更多
The edges between vertices in networks take not only the common binary values, but also the ordered values in some situations(e.g., the measurement of the relationship between people from worst to best in social netwo...The edges between vertices in networks take not only the common binary values, but also the ordered values in some situations(e.g., the measurement of the relationship between people from worst to best in social networks). In this paper, the authors study the asymptotic property of the moment estimator based on the degrees of vertices in ordered networks whose edges are ordered random variables. In particular, the authors establish the uniform consistency and the asymptotic normality of the moment estimator when the number of parameters goes to infinity. Simulations and a real data example are provided to illustrate asymptotic results.展开更多
Connection Admission Control(CAC)in ATM networks is the set o/actions taken by the networkto decide whether to accept connection requests during the phase of call establishment or call re-negotiation.CAC is an integra...Connection Admission Control(CAC)in ATM networks is the set o/actions taken by the networkto decide whether to accept connection requests during the phase of call establishment or call re-negotiation.CAC is an integral part of the preventive congestion control in ATM networks whose aim is to ensurenetwork performance.The CAC algorithm has the characteristics of the multitude of control parameters,high degree of computation complexity and strong time restrictions.In this paper we present a CACmechanism featured by combination of foreground control and background learning which is based onneural networks having the capabilities of self-learning and high-Speed processing.A case study is given,after which we discuss the practicability of the proposed algorithm.展开更多
Traditional algorithms do not fully utilize the timing information of non-cooperative targets,and setting too many motion parameters can lead to complex dynamic model calculations.This paper proposes a long short-term...Traditional algorithms do not fully utilize the timing information of non-cooperative targets,and setting too many motion parameters can lead to complex dynamic model calculations.This paper proposes a long short-term memory(LSTM)network-based method for estimating the parameters of the active segment of the non-cooperative target under single-satellite observation.Based on the simulation training set of the active segment of the non-cooperative target,the network parameters of the LSTM network are designed,the motion characteristics of the active segment of the non-cooperative target are fully excavated through data-driven methods,and the candidate cutting trajectories are screened and predicted to realize the estimation of the motion parameters of the active segment of the non-cooperative target under the condition of single-satellite observation.The experimental results show that the estimation method proposed in this paper can effectively deal with the inaccurate problem with the non-cooperative target’s active segment motion model established under the condition of single-satellite observation,obtain more accurate active segment motion parameters,and provide a feasible new idea and method for the parameter estimation of the active segment of the non-cooperative target under the single-satellite observation.展开更多
A parametric optimization method is proposed in the design of a high-efficiency free-form illumination system. The proposed method is intended to provide rectangular uniform illumination with a light emitting diode （...A parametric optimization method is proposed in the design of a high-efficiency free-form illumination system. The proposed method is intended to provide rectangular uniform illumination with a light emitting diode （LED） source. An initial illumination system is first constructed and parameterized. The parameters of the initial system are optimized according to actual simulation results, and one design sample is presented. A liquid crystal on silicon （LCoS） micro-projector test module is fabricated and tested based on the design sample. Compared with the conventional micro-projectors using rotational symmetry devices, the micro-projector system designed with the parametric optimization method can send 1.65 times the source power to the LCoS active area with a 4：3 target ratio, and the unilormity reaches 98%.展开更多
基金co-supported by the National Natural Science Foundation of China(No.52192633)the Natural Science Foundation of Shaanxi Province,China(No.2022JC-03)the Fundamental Research Funds for the Central Universities,China(No.XJSJ23164)。
文摘To effectively estimate the unknown aerodynamic parameters from the aircraft’s flight data,this paper proposes a novel aerodynamic parameter estimation method incorporating a stacked Long Short-Term Memory(LSTM)network model and the Levenberg-Marquardt(LM)method.The stacked LSTM network model was designed to realize the aircraft dynamics modeling by utilizing a frame of nonlinear functional mapping based entirely on the measured input-output data of the aircraft system without requiring explicit postulation of the dynamics.The LM method combines the already-trained LSTM network model to optimize the unknown aerodynamic parameters.The proposed method is applied by using the real flight data,generated by ATTAS aircraft and a bio-inspired morphing Unmanned Aerial Vehicle(UAV).The investigation reveals that for the two different flight data,the designed stacked LSTM network structure can maintain the efficacy of the network prediction capability only by appropriately adjusting the dropout rates of its hidden layers without changing other network parameters(i.e.,the initial weights,initial biases,number of hidden cells,time-steps,learning rate,and number of training iterations).Besides,the proposed method’s effectiveness and potential are demonstrated by comparing the estimated results of the ATTAS aircraft or the bio-inspired morphing UAV with the corresponding reference values or wind-tunnel results.
基金This work was supported in part by the national natural science foundation of China(51677059)Guangdong Power Grid Company Limited Project.(GDKJXM00000025)。
文摘The simulation precision of the classic load model(CLM)is affected by the increasing proportion of installed energy storage capacity in the grid.This paper studies the all-vanadium redox flow battery(VRB)and proposes an equivalent model based on the measurement-based load modeling method,which can simulate the maximum output of the VRB energy storage system and fit the external characteristic of the system precisely in the occurrence of large disturbance and continuous small disturbance.The equivalent model is connected to CLM to form a generalized synthesis load model(GSLM),which considers the parameters of distribution network and reactive power compensation.Compared with CLM,GSLM has better structures and can describe the load characteristics of distribution network with energy storage system more precisely.Simulation results validate the effectiveness and good parameter stability of GSLM,and show that the higher the proportion of energy storage in the grid is the better description ability GSLM has.
基金supported by the "Light of West China" Program of Chinese Academy of Sciences (Grant No.Y6R2250250)the National Basic Research Program of China (973 Program, Grant No.2013CB733201)+2 种基金the One-Hundred Talents Program of Chinese Academy of Sciences (LijunSu)the Key Research Program of Frontier Sciences, Chinese Academy of Sciences (Grant No.QYZDB-SSW-DQC010)the Youth Fund of Institute of Mountain Hazards and Environment, Chinese Academy of Sciences (Grant No. Y6K2110110)
文摘Xigeda formation is a type of hundredmeter-thick lacustrine sediments of being prone to triggering landslides along the trunk channel and tributaries of the upper Yangtze River in China. The Yonglang landslide located near Yonglang Town of Dechang County in Sichuan Province of China, which was a typical Xigeda formation landslide, was stabilized by anti-slide piles. Loading tests on a loading-test pile were conducted to measure the displacements and moments. The uncertainty of the tested geomechanical parameters of the Yonglang landslide over certain ranges would be problematic during the evaluation of the landslide. Thus, uniform design was introduced in the experimental design,and by which, numerical analyses of the loading-test pile were performed using Fast Lagrangian Analysis of Continua(FLAC3D) to acquire a database of the geomechanical parameters of the Yonglang landslide and the corresponding displacements of the loadingtest pile. A three-layer back-propagation neural network was established and trained with the database, and then tested and verified for its accuracy and reliability in numerical simulations. Displacement back analysis was conducted by substituting the displacements of the loading-test pile to the well-trained three-layer back-propagation neural network so as to identify the geomechanical parameters of the Yonglang landslide. The neuralnetwork-based displacement back analysis method with the proposed methodology is verified to be accurate and reliable for the identification of the uncertain geomechanical parameters of landslides.
文摘Superconductive properties for oxides were predicted by artificial neural network (ANN) method with structural and chemical parameters as inputs. The predicted properties include superconductivity for oxides, distributed ranges of the superconductive transition temperature (Tc) for complex oxides, and Tc values for cuprate superconductors. The calculated results indicated that the adjusted ANN can be used to predict superconductive properties for unknown oxides.
基金the National Natural Science Foundation of China (Nos.19872002 and 10272003)Climbing Foundation of Northern Jiaotong University
文摘The multi- layers feedforward neural network is used for inversion ofmaterial constants of fluid-saturated porous media. The direct analysis of fluid-saturated porousmedia is carried out with the boundary element method. The dynamic displacement responses obtainedfrom direct analysis for prescribed material parameters constitute the sample sets training neuralnetwork. By virtue of the effective L-M training algorithm and the Tikhonov regularization method aswell as the GCV method for an appropriate selection of regu-larization parameter, the inversemapping from dynamic displacement responses to material constants is performed. Numerical examplesdemonstrate the validity of the neural network method.
基金supported by National Natural Science Foundation of China under Grant No.60802016, 60972010by China Next Generation Internet (CNGI) project under Grant No.CNGI-09-03-05
文摘A complete study for the implementation of wireless sensor networks in the intelligent building is presented. We carry out some experiments to find out the factors affecting the network performance. Several vital parameters which are related to the link quality are measured before deploying the actual system. And then, we propose an optimized routing protocol based on the analysis of the test data. We evaluate the deployment strategies to ensure the excellent performance of the wireless sensor networks under the real working conditions. And the evaluation results show that the presented system could satisfy the requirements of the applications in the intelligent building.
基金funding from the Ministry of Science and Technology of the People’s Republic of China (2013CB956000)the National Natural Science Foundation of China (41130533)
文摘Dune networks are widely distributed in the world＇s deserts,which include primary ridges and secondary ridges.However,they have not been sufficiently studied in a systematic manner and their origins and spatial and morphological characteristics remain unclear.To provide information on the geomorphology of dune networks,we analyze the software geomorphologic patterns of the dune networks in China＇s Tengger Desert using matrix and laboratory to process remote-sensing images.Based on analysis of image features and their layout in a topographic map,we identify two types of dune networks （square and rectangular dune networks） with different size and morphological structures in the Tengger Desert.Four important geomorphic pattern parameters,ridge length,spacing,orientation and defect density,are analyzed.The length of primary ridges of dune networks decreases from northwest of the desert to the southeast,resulting an increasing spacing and a transition from rectangular dune networks to square dune networks.Wind regime and sediment supply are responsible for the variation in pattern parameters.We use the spacing and defect density data to estimate the construction time of dune networks and found that the dune networks in the Tengger Desert formed since about 1.3 ka BP.
文摘In large mines,single fan is usually not enough to ventilate all the working areas.Single mine-fan approach cannot be directly applied to multiple-fan networks because the present of multiple pressures and air quantities associated with each fan in the network.Accordingly,each fan in a multiple-fan system has its own mine characteristic curve,or a subsystem curve.Under some consideration,the conventional concept of a mine characteristic curve of a single-fan system can be directly extended to that of a particular fan within a multiple-fan system.In this paper the mutual effect of the fans on each other and their effect on the stability of the ventilation network were investigated by Hardy Cross algorithm combined with a switching-parameters technique.To show the validity and reliability of this algorithm,the stability of the ventilation system of Abu-Tartur Mine(one of the largest underground mine in Egypt)has been studied.
基金Sci-Tech Planning Projects of Chongqing City,China(No.CSTC2007AA7003).
文摘A sequential diagnosis method is proposed based on a fuzzy neural network realized by ＂the partially-linearized neural network （PNN）＂, by which the fault types of rotating machinery can be precisely and effectively distinguished at an early stage on the basis of the possibilities of symptom parameters. The non-dimensional symptom parameters in time domain are defined for reflecting the features of time signals measured for the fault diagnosis of rotating machinery. The synthetic detection index is also proposed to evaluate the sensitivity of non-dimensional symptom parameters for detecting faults. The practical example of condition diagnosis for detecting and distinguishing fault states of a centrifugal pump system, such as cavitation, impeller eccentricity which often occur in a centrifugal pump system, are shown to verify the efficiency of the method proposed in this paper.
基金supported by the research-applied project of Astronomical Institute,State Committee on Science and Technologyof Uzbekistan(FA-A5-F014)
文摘This study is focused on the discussion of a modern GNSS network and datum in Uzbekistan. Considering the significance difference （up to 200 m） in positions of the local ellipsoidal datum and the global datum, the precise transformation parameters between national geodetic datum CS-42, and the World Geodetic System 1984 （WGS84） global datum used by the GPS is estimated. This study aims to evaluate the ac- curacy of the currently used transformation parameters from different sources in the region, and give preliminary recommendations for using these sets also. The differences between transformed, original and WGS-84 coordinates were calculated and evaluated. On the basis of this difference, different zones for determination of transformation parameters have been proposed.This study is focused on the discussion of a modern GNSS network and datum in Uzbekistan. Considering the significance difference （up to 200 m） in positions of the local ellipsoidal datum and the global datum, the precise transformation parameters between national geodetic datum CS-42, and the World Geodetic System 1984 （WGS84） global datum used by the GPS is estimated. This study aims to evaluate the accuracy of the currently used transformation parameters from different sources in the region, and give preliminary recommendations for using these sets also. The differences between transformed, original and WGS-84 coordinates were calculated and evaluated. On the basis of this difference, different zones for determination of transformation parameters have been proposed.
基金supported by National Natural Science Foundation of China(61273108)the Fundamental Research Funds for the Central Universities(106112013CDJZR175501)the Scientific Research Foundation for the Returned Overseas Chinese Scholars,State Education Ministry
文摘The multicast routing problem with multiple QoS constraints in networks with uncertain parameters is discussed, and a network model that is suitable to research such QoS multicast routing problem is described. The QMRGA, a multicast routing policy for Internet, mobile network or other highperformance networks is mainly presented, which is based on the genetic algorithm(GA), and can provide QoSsensitive paths in a scalable and flexible way in the network environment with uncertain parameters. The QMRGA can also optimize the network resources such as bandwidth and delay, and can converge to the optimal or nearoptimal solution within few iterations, even for the network environment with uncertain parameters. The incremental rate of computational cost can be close to a polynomial and is less than exponential rate. The performance measures of the QMRGA are evaluated by using simulations. The results show that QMRGA provides an available approach to QoS multicast routing in network environment with uncertain parameters.
基金This project is supported by National Natural Science Foundation of China (No.60304015, No.50575142).
文摘A new parameter coordination and robust optimization approach for multidisciplinary design is presented. Firstly, the constraints network model is established to support engineering change, coordination and optimization. In this model, interval boxes are adopted to describe the uncertainty of design parameters quantitatively to enhance the design robustness. Secondly, the parameter coordination method is presented to solve the constraints network model, monitor the potential conflicts due to engineering changes, and obtain the consistency solution space corresponding to the given product specifications. Finally, the robust parameter optimization model is established, and genetic arithmetic is used to obtain the robust optimization parameter. An example of bogie design is analyzed to show the scheme to be effective.
文摘In this paper, multimodel and neural emulators are proposed for uncoupled multivariable nonlinear plants with unknown dynamics. The contributions of this paper are to extend the emulators to multivariable non square systems and to propose a systematic method to compute the multimodel synthesis parameters. The effectiveness of the proposed emulators is shown through two simulation examples. The obtained results are very satisfactory, they illustrate the performance of both emulators and show the advantages of the multimodel emulator relatively to the neural one.
文摘Heat and thermal problems are major obstacles to achieving high power density in compact permanent magnet(PM)topologies.Consequently,a comprehensive,accurate,and rapid temperature rise estimation method is required for novel electric machines to ensure safe and reliable operations.A unique three-dimensional(3D)lumped parameter thermal network(LPTN)is presented for accurate thermal modeling of a newly developed outer-rotor hybrid-PM flux switching generator(OR-HPMFSG)for direct-drive applications.First,the losses of the OR-HPMFSG are calculated using 3D finite element analysis(FEA).Subsequently,all machine components considering the thermal contact resistance,anisotropic thermal conductivity of materials,and various heat flow paths are comprehensively modeled based on the thermal resistances.In the proposed 3-D LPTN,internal nodes are considered to predict the average temperature as well as the hot spots of all active and passive components.Experimental measurements are performed on a prototype OR-HPMFSG to validate the efficiency of the 3-D LPTN.A comparison of the results at various operating points between the developed 3-D LPTN,experimental test,and FEA indicates that the 3-D LPTN quickly approximates the hotspot and mean temperature of all components under both transient and steady states with high accuracy.
基金supported by the Research Fund of Science and Technology Innovation 2030-Major Project(Grant No.2021ZD0201600)the Research Fund of PLA of China(Grant Nos.AWS17J011 and BWS17J024)。
文摘Neural activity extraction and neural decoding from neural signals are an important part of critical components of brain-computer interface systems.With the development of brain-computer interface technology,the demand for precise external control and nervous activities in macaque monkey during unilateral hand grasp has increased the complexity of control and neural decoding,which puts forward higher requirements for the accuracy and stability of feature extraction and neural decoding.In this study,a micro Capsnet network architecture that consists of a few network layers,a vector feature structure,and optimization network parameters,is proposed to decrease the computing time and complexity,decrease artificial debugging,and improve the decoding accuracy.Compared with KNN,SVM,XGBOOST,CNN,Simple RNN,and LSTM,the algorithm in this study improves the decoding accuracy by 98.03%,and achieves state-of-the-art accuracy and stronger robustness.Furthermore,the proposed algorithm can further enhance the control accuracy in the brain-computer interface.
基金supported by the National Natural Science Foundation of China under Grant Nos.11271147,11471135partially supported by the National Natural Science Foundation of China under Grant No.11401239+1 种基金Funds of CCNU from the Colleges’s Basic Research and Operation of MOE(CCNU15A02032,CCNU15ZD011)a Fund from KLAS(130026507)
文摘The edges between vertices in networks take not only the common binary values, but also the ordered values in some situations(e.g., the measurement of the relationship between people from worst to best in social networks). In this paper, the authors study the asymptotic property of the moment estimator based on the degrees of vertices in ordered networks whose edges are ordered random variables. In particular, the authors establish the uniform consistency and the asymptotic normality of the moment estimator when the number of parameters goes to infinity. Simulations and a real data example are provided to illustrate asymptotic results.
文摘Connection Admission Control(CAC)in ATM networks is the set o/actions taken by the networkto decide whether to accept connection requests during the phase of call establishment or call re-negotiation.CAC is an integral part of the preventive congestion control in ATM networks whose aim is to ensurenetwork performance.The CAC algorithm has the characteristics of the multitude of control parameters,high degree of computation complexity and strong time restrictions.In this paper we present a CACmechanism featured by combination of foreground control and background learning which is based onneural networks having the capabilities of self-learning and high-Speed processing.A case study is given,after which we discuss the practicability of the proposed algorithm.
基金supported by the National Natural Science Foundation of China under grant 42271448by the Key Laboratory of Land satellite Remote sensing Application,Ministry of Natural Resources of the People’s Republic of China(Grant No.KLSMNR-G202317).
文摘Traditional algorithms do not fully utilize the timing information of non-cooperative targets,and setting too many motion parameters can lead to complex dynamic model calculations.This paper proposes a long short-term memory(LSTM)network-based method for estimating the parameters of the active segment of the non-cooperative target under single-satellite observation.Based on the simulation training set of the active segment of the non-cooperative target,the network parameters of the LSTM network are designed,the motion characteristics of the active segment of the non-cooperative target are fully excavated through data-driven methods,and the candidate cutting trajectories are screened and predicted to realize the estimation of the motion parameters of the active segment of the non-cooperative target under the condition of single-satellite observation.The experimental results show that the estimation method proposed in this paper can effectively deal with the inaccurate problem with the non-cooperative target’s active segment motion model established under the condition of single-satellite observation,obtain more accurate active segment motion parameters,and provide a feasible new idea and method for the parameter estimation of the active segment of the non-cooperative target under the single-satellite observation.
文摘A parametric optimization method is proposed in the design of a high-efficiency free-form illumination system. The proposed method is intended to provide rectangular uniform illumination with a light emitting diode （LED） source. An initial illumination system is first constructed and parameterized. The parameters of the initial system are optimized according to actual simulation results, and one design sample is presented. A liquid crystal on silicon （LCoS） micro-projector test module is fabricated and tested based on the design sample. Compared with the conventional micro-projectors using rotational symmetry devices, the micro-projector system designed with the parametric optimization method can send 1.65 times the source power to the LCoS active area with a 4：3 target ratio, and the unilormity reaches 98%.
