提出了一种基于Monte Carlo方法的多机器人自定位方法.该方法在机器人进行自定位时,对用来估计机器人位置的MCL(Monte Carlo Localization)粒子空间进行栅格划分,然后采用可变栅格法获得能代表所有粒子整体特性的特征粒子集.因为特征粒...提出了一种基于Monte Carlo方法的多机器人自定位方法.该方法在机器人进行自定位时,对用来估计机器人位置的MCL(Monte Carlo Localization)粒子空间进行栅格划分,然后采用可变栅格法获得能代表所有粒子整体特性的特征粒子集.因为特征粒子的数量较粒子总数大大减少,该方法能避免直接将Monte Carlo方法应用于多机器人定位中产生的维数灾的问题,可以在保证精度的情况下降低运算复杂度.仿真结果表明,该方法能较好地满足多机器人自定位的要求.展开更多
The characteristics of the flowfields of a synthetic jet actuator are experimentally investigated with the slot-nozzle driven by the piezoelectric membrane. The particle image velocimetry （PIV） and the hot-wire anem...The characteristics of the flowfields of a synthetic jet actuator are experimentally investigated with the slot-nozzle driven by the piezoelectric membrane. The particle image velocimetry （PIV） and the hot-wire anemometer are utilized to measure the flowfields and the velocity profiles of the actuator with different actuating factors. Analytical results show that pairs of counter-rotating vortices are generated near the nozzle. With the development of the synthetic ject, the synthetic jet rapidly spreads in the slot-width direction; while in the slot-length direction, it contracts firstly and slowly spreads. The centerline velocity distribution has a up-down tendency varying with axial distances, and accelerates to its maximum at z/b= 10. The transverse velocity profile across the slot-width is centro-symmetric and self-similar. However, the velocity profiles across the slot-length are saddle-like near the nozzle. It shows that there are two resonance frequencies for the actuator. If the actuator works with the resonance frequency, the vorticity and the velocity of the synthetic jet are higher than those of other frequencies. Compared with the continuous jet, the synthetic jet shows special flow characteristics.展开更多
The strength and failure characteristics of most natural rock mass are influenced by discontinues such as fissures, joints, and weak surfaces. In the present study, the strength and failure behavior of ubiquitous- joi...The strength and failure characteristics of most natural rock mass are influenced by discontinues such as fissures, joints, and weak surfaces. In the present study, the strength and failure behavior of ubiquitous- joint rock-l!ke specimens under uniaxial loading have been investigated by DIC （digital image correlation） and discrete element numerical method （PFC2D）. The results are obtained. Firstly, the UCSJ of spec- imens with γ= 15° or 30° shows similar tendency while α goes from 0° to 75°. With γ= 45° or 60°, the UCSJ of specimens increases when α goes from 0° to 30° and decreases after α goes beyond 30°. With γ=75°, the peak UCSJ value is reached when α=0°. The UCSJ value shows an increasing trend when α goes from 60° to 75°. Secondly, the ubiquitous-joint specimens present different failure modes for various levels of α and γ（β-α）. Based on the experimental results, the failure mode of ubiquitous-joint specimens can be classified into three categories： stepped path failure, failure through parallel plane, and failure through cross plane.展开更多
Two kinds of Al based functionally gradient composite tubes reinforced by primary Si particles alone and primary Si/in situ Mg2Si particles jointly were successfully prepared by centrifugal casting,and their structura...Two kinds of Al based functionally gradient composite tubes reinforced by primary Si particles alone and primary Si/in situ Mg2Si particles jointly were successfully prepared by centrifugal casting,and their structural and mechanical characters were compared.It is found that the composite reinforced with primary Si particles takes a characteristic of particles distribution both in the inner and outer layers.However,composite reinforced with primary Si/Mg2Si particles jointly takes a characteristic of particles distribution only in the inner layer and shows a sudden change of particles distribution across the section of inner and outer layers.The hardness and wear resistance of Al-19Si-5Mg tube in the inner layer are greatly higher than that in the other layers of Al-19Si-5Mg tube and Al-19Si tube.Theoretical analysis reveals that the existence of Mg2Si particles is the key factor to form this sudden change of gradient distribution of two kinds of particles.Because Mg2Si particles with a lower density have a higher centripetal moving velocity than primary Si particles,in a field of centrifugal force,they would collide with primary Si particles and then impel the later to move together forward to the inner layer of the tube.展开更多
Binary particle swarm optimization algorithm(BPSOA) has the excellent characters such as easy to implement and few set parameters.But it is tendentious to stick in the local optimal solutions and has slow convergence ...Binary particle swarm optimization algorithm(BPSOA) has the excellent characters such as easy to implement and few set parameters.But it is tendentious to stick in the local optimal solutions and has slow convergence rate when the problem is complex.Cultural algorithm(CA) can exploit knowledge extracted during the search to improve the performance of an evolutionary algorithm and show higher intelligence in treating complicated problems.So it is proposed that integrating binary particle swarm algorithm into cultural algorithm frame to develop a more efficient cultural binary particle swarm algorithm (CBPSOA) for fault feature selection.In CBPSOA,BPSOA is used as the population space of CA;the evolution of belief space adopts crossover,mutation and selection operations;the designs of acceptance function and influence function are improved according to the evolution character of BPSOA.The tests of optimizing functions show the proposed algorithm is valid and effective.Finally,CBPSOA is applied for fault feature selection.The simulations on Tennessee Eastman process (TEP) show the CBPSOA can perform better and more quickly converge than initial BPSOA.And with fault feature selection,more satisfied performance of fault diagnosis is obtained.展开更多
In order to diagnose the common faults of railway switch control circuit,a fault diagnosis method based on density-based spatial clustering of applications with noise(DBSCAN)and self-organizing feature map(SOM)is prop...In order to diagnose the common faults of railway switch control circuit,a fault diagnosis method based on density-based spatial clustering of applications with noise(DBSCAN)and self-organizing feature map(SOM)is proposed.Firstly,the three-phase current curve of the switch machine recorded by the micro-computer monitoring system is dealt with segmentally and then the feature parameters of the three-phase current are calculated according to the action principle of the switch machine.Due to the high dimension of initial features,the DBSCAN algorithm is used to separate the sensitive features of fault diagnosis and construct the diagnostic sensitive feature set.Then,the particle swarm optimization(PSO)algorithm is used to adjust the weight of SOM network to modify the rules to avoid“dead neurons”.Finally,the PSO-SOM network fault classifier is designed to complete the classification and diagnosis of the samples to be tested.The experimental results show that this method can judge the fault mode of switch control circuit with less training samples,and the accuracy of fault diagnosis is higher than that of traditional SOM network.展开更多
We construct four linear composite operators for a two-particle system and give common eigenvectors of those operators. The technique of integration within an ordered product of operators is employed to prove that tho...We construct four linear composite operators for a two-particle system and give common eigenvectors of those operators. The technique of integration within an ordered product of operators is employed to prove that those common eigenvectors are complete and orthonormal. Therefore, a new intermediate coordinate-momentum representation for a two-particle system is proposed and applied to some two-body dynamic problems.展开更多
文摘提出了一种基于Monte Carlo方法的多机器人自定位方法.该方法在机器人进行自定位时,对用来估计机器人位置的MCL(Monte Carlo Localization)粒子空间进行栅格划分,然后采用可变栅格法获得能代表所有粒子整体特性的特征粒子集.因为特征粒子的数量较粒子总数大大减少,该方法能避免直接将Monte Carlo方法应用于多机器人定位中产生的维数灾的问题,可以在保证精度的情况下降低运算复杂度.仿真结果表明,该方法能较好地满足多机器人自定位的要求.
文摘The characteristics of the flowfields of a synthetic jet actuator are experimentally investigated with the slot-nozzle driven by the piezoelectric membrane. The particle image velocimetry （PIV） and the hot-wire anemometer are utilized to measure the flowfields and the velocity profiles of the actuator with different actuating factors. Analytical results show that pairs of counter-rotating vortices are generated near the nozzle. With the development of the synthetic ject, the synthetic jet rapidly spreads in the slot-width direction; while in the slot-length direction, it contracts firstly and slowly spreads. The centerline velocity distribution has a up-down tendency varying with axial distances, and accelerates to its maximum at z/b= 10. The transverse velocity profile across the slot-width is centro-symmetric and self-similar. However, the velocity profiles across the slot-length are saddle-like near the nozzle. It shows that there are two resonance frequencies for the actuator. If the actuator works with the resonance frequency, the vorticity and the velocity of the synthetic jet are higher than those of other frequencies. Compared with the continuous jet, the synthetic jet shows special flow characteristics.
基金funding from Project (Nos.51474249 and 51404179) supported by National Natural Science Foundation of ChinaProject Supported by Innovation Driven Plan of Central South University of China (No.2016CX019)Project (No. SKLGDUEK1405) funded by the Open Projects of State Key Laboratory for Geo-mechanics and Deep Underground Engineering of China University of Mining and Technology,in China
文摘The strength and failure characteristics of most natural rock mass are influenced by discontinues such as fissures, joints, and weak surfaces. In the present study, the strength and failure behavior of ubiquitous- joint rock-l!ke specimens under uniaxial loading have been investigated by DIC （digital image correlation） and discrete element numerical method （PFC2D）. The results are obtained. Firstly, the UCSJ of spec- imens with γ= 15° or 30° shows similar tendency while α goes from 0° to 75°. With γ= 45° or 60°, the UCSJ of specimens increases when α goes from 0° to 30° and decreases after α goes beyond 30°. With γ=75°, the peak UCSJ value is reached when α=0°. The UCSJ value shows an increasing trend when α goes from 60° to 75°. Secondly, the ubiquitous-joint specimens present different failure modes for various levels of α and γ（β-α）. Based on the experimental results, the failure mode of ubiquitous-joint specimens can be classified into three categories： stepped path failure, failure through parallel plane, and failure through cross plane.
基金Project(2008BB4177) supported by the Natural Science Foundation of Chongqing,China
文摘Two kinds of Al based functionally gradient composite tubes reinforced by primary Si particles alone and primary Si/in situ Mg2Si particles jointly were successfully prepared by centrifugal casting,and their structural and mechanical characters were compared.It is found that the composite reinforced with primary Si particles takes a characteristic of particles distribution both in the inner and outer layers.However,composite reinforced with primary Si/Mg2Si particles jointly takes a characteristic of particles distribution only in the inner layer and shows a sudden change of particles distribution across the section of inner and outer layers.The hardness and wear resistance of Al-19Si-5Mg tube in the inner layer are greatly higher than that in the other layers of Al-19Si-5Mg tube and Al-19Si tube.Theoretical analysis reveals that the existence of Mg2Si particles is the key factor to form this sudden change of gradient distribution of two kinds of particles.Because Mg2Si particles with a lower density have a higher centripetal moving velocity than primary Si particles,in a field of centrifugal force,they would collide with primary Si particles and then impel the later to move together forward to the inner layer of the tube.
基金National High Technology Research and Development Program of China(No.2007AA04Z171)
文摘Binary particle swarm optimization algorithm(BPSOA) has the excellent characters such as easy to implement and few set parameters.But it is tendentious to stick in the local optimal solutions and has slow convergence rate when the problem is complex.Cultural algorithm(CA) can exploit knowledge extracted during the search to improve the performance of an evolutionary algorithm and show higher intelligence in treating complicated problems.So it is proposed that integrating binary particle swarm algorithm into cultural algorithm frame to develop a more efficient cultural binary particle swarm algorithm (CBPSOA) for fault feature selection.In CBPSOA,BPSOA is used as the population space of CA;the evolution of belief space adopts crossover,mutation and selection operations;the designs of acceptance function and influence function are improved according to the evolution character of BPSOA.The tests of optimizing functions show the proposed algorithm is valid and effective.Finally,CBPSOA is applied for fault feature selection.The simulations on Tennessee Eastman process (TEP) show the CBPSOA can perform better and more quickly converge than initial BPSOA.And with fault feature selection,more satisfied performance of fault diagnosis is obtained.
基金High Education Research Project Funding(No.2018C-11)Natural Science Fund of Gansu Province(Nos.18JR3RA107,1610RJYA034)Key Research and Development Program of Gansu Province(No.17YF1WA 158)。
文摘In order to diagnose the common faults of railway switch control circuit,a fault diagnosis method based on density-based spatial clustering of applications with noise(DBSCAN)and self-organizing feature map(SOM)is proposed.Firstly,the three-phase current curve of the switch machine recorded by the micro-computer monitoring system is dealt with segmentally and then the feature parameters of the three-phase current are calculated according to the action principle of the switch machine.Due to the high dimension of initial features,the DBSCAN algorithm is used to separate the sensitive features of fault diagnosis and construct the diagnostic sensitive feature set.Then,the particle swarm optimization(PSO)algorithm is used to adjust the weight of SOM network to modify the rules to avoid“dead neurons”.Finally,the PSO-SOM network fault classifier is designed to complete the classification and diagnosis of the samples to be tested.The experimental results show that this method can judge the fault mode of switch control circuit with less training samples,and the accuracy of fault diagnosis is higher than that of traditional SOM network.
基金supported by the Natural Science Foundation of Heze Universityof Shandong Province of China under Grant Nos.XY07WL01 and XY08WL03the University Experimental Technology Foundation of Shandong Province under Grant No.S04W138+1 种基金the Natural Science Foundation of Shandong Province under Grant No.Y2008A16the National Natural Science Foundation of China under Grant No.10574060
文摘We construct four linear composite operators for a two-particle system and give common eigenvectors of those operators. The technique of integration within an ordered product of operators is employed to prove that those common eigenvectors are complete and orthonormal. Therefore, a new intermediate coordinate-momentum representation for a two-particle system is proposed and applied to some two-body dynamic problems.
