Study on launch dynamics of the tank marching fire

As an army main battle equipment, it is required that the tank should have high firing accuracy and high first round hit probability during marching. The initial disturbance of the projectile is the premier factor that takes effect on the marching fire accuracy of the tank. And the marching fire accuracy of the tank depends on the launch dynamics behaviors of the tank. In this paper, the launch dynamics theory of a tank marching fire is studied, and its launch dynamics model is established. Based on the transfer matrix method for multibody system(MSTMM) and the automatic deduction theorem of overall transfer equations, the overall transfer equation and the overall transfer matrix of a tank multibody system are deduced; the launch dynamics equations of the tank marching fire are deduced, and the dynamic response of the tank system, the motion of projectile in barrel, the initial disturbance of the projectile and the vertical target dispersion are exactly simulated; meanwhile, the results of simulation are verified by tests. This work provides both theoretical foundation and simulation approaches for improving the marching fire accuracy of the tank.     

神经网络在多目标分布式融合中的应用研究

提出了适合分布式多传感器多目标(MSMT)数据融合估计算法，对这种推广的分层融合估计算法进行了数学推导和描述，研究了利用神经网络进行MSMT跟踪融合的网络结构和算法，进行了计算机模拟仿真。仿真结果表明神经网络融合估计可提高跟踪精度，并且这种融合方法是有效的。     

采用直线电机车辆的轨道交通耦合动力学模型及仿真分析

建立了采用直线电机车辆的轨道交通的车-线耦合动力学模型,并与车辆动力学分析通用软件ADAMS /Rail进行了比较,从而验证了所建模型的正确性.通过对广州市轨道交通4号线工程线路设计参数进行的仿真计算,给出了相应的建议值。     

大断面深浅埋黄土隧道围岩压力试验研究

研究目的:针对郑州至西安客运专线黄土隧道设计中存在的问题,开展大断面黄土隧道深浅埋分界、深浅埋围岩压力计算研究,提出大断面黄土隧道深浅埋分界高度;确定深浅埋黄土隧道围岩压力计算方法;明确深浅埋黄土隧道二次衬砌厚度的设计原则,指导郑州至西安客运专线黄土隧道的设计与施工,并为类似大断面黄土隧道工程的设计提供技术支持. 研究结论:通过对大断面深浅埋黄土隧道围岩压力的试验研究,提出了郑州至西安客运专线大断面黄土隧道深浅埋分界高度、围岩压力计算方法和二次衬砌厚度的设计原则.郑州至西安客运专线黄土隧道深浅埋分界高度应为40～60 m;浅埋黄土隧道荷载按谢家烋公式计算,深埋黄土隧道荷载按太沙基理论计算;不同埋深黄土隧道二次衬砌宜采用相同厚度.     

气泡混合土抗冻融循环性能试验研究

为解决冻土地区普通路基由于保温性能差导致的路基病害问题,采用保温隔热性能好的气泡混合土作为路基填料,可起到保护冻土、减少病害的作用。为探讨气泡混合土的抗冻性能,选取了不同容重的气泡混合土试件进行冻融循环试验研究,研究气泡混合土质量及强度损失规律,从而获知气泡混合土的容重对其抗冻性能的影响;进而,向气泡混合土试件中掺入玻璃纤维,探讨其对气泡混合土抗冻性能的增强作用。结果表明：气泡混合土的抗冻性能随着容重的增大而提高,表现为容重越大,所能经受的冻融循环次数越多,抗压强度和质量损失率越低;容重为800kg/m3的气泡混合土试件经过15次冻融循环后抗压强度迅速降低,经过100次冻融循环后,试件的质量损失达到9.2%;而容重为1 200kg/m3的气泡混合土试件在经过50次冻融循环后,抗压强度才开始明显降低,经过100次冻融循环后,试件的质量损失只有4.5%。玻璃纤维能显著提高气泡混合土的抗冻性能,其抗压强度损失率和质量损失率明显较未掺纤维的普通气泡混合土要小,且抗压强度和质量损失的速率明显降低;不同容重的气泡混合土试件掺入纤维后,经过50次冻融循环后,试件的抗压强度损失减少50%以上,质量损失减少40%以上。     

双支撑工作模式下TBM撑靴与围岩接触仿真

撑靴为TBM的前进及稳定性提供保障,与围岩的接触是否均匀直接影响工作的稳定性,针对撑靴与围岩接触会因为应力分布不均匀而导致支撑不稳或围岩坍塌等问题,以新型TBM的撑靴为研究对象,根据试验台的三维模型创建撑靴和其他机构之间的力传递特性,建立双支撑工作模式下撑靴与围岩的接触模型,采用有限元方法研究撑靴与围岩接触面应力、位移分布。结果表明:撑靴与围岩的综合应力分布较为均匀,在周向尺寸上分布在-18°～18°范围内,撑靴接触表面最大应力为13.3 MPa,围岩接触表面最大应力为4.03 MPa。撑靴接触表面综合位移中间小、两端大,而在围岩接触表面综合位移中间大,向四周位移逐渐减小。并且运用赫兹公式对有限元分析的结果进行验证,误差为0.5 MPa,表明分析结果可靠,为提高整机稳定性提供了参考。     

Geometric calibration algorithm of polarization camera using planar patterns

Polarization pattern provides additional information besides spectral signatures. It can be used in many applications, such as navigation, defect detection and object identification. A novel polarization camera composed of four synchronized cameras is proposed, and it can realize real-time polarization measurement. This study particularly concentrates on the geometric calibration of the system. The projection model is analyzed and the multi-camera calibration algorithm is proposed. Firstly, each camera is calibrated separately using planar patterns, and then the geometric calibration algorithms are performed. Due to the geometrical constraint, a global optimization method results in smaller estimation uncertainties. A mean rotation error of 0.025° and a mean translation error of 0.26mm are achieved after geometric calibration. The images are rectified to establish a correspondence among cameras and are combined to acquire the polarization measurement. The polarization pattern of the skylight is measured by the system and the results are consistent with the previous studies.     

Research of legal affair simulation based on Petri net

Legal affair simulation is on the basis of information technology, and can simulate legal scene. College students do legal experiments with virtual reality scene. This helps to train college students. Petri net has not only strict math definition to analyze the dynamic behavior of models, but also intuitive graphic expression. Petri net is used to model for legal process. Reduction rules of Petri net are used to analyze the correctness of the system. At last Java Business Process Management (JBPM) technology is used to realize legal affair simulation models, models are transformed into flow charts. Simulation software deduces processes of legal affair. Many college students have improved their ability with the software, the fact proves that the method is effective.     

Magnetic field tuning characteristics of bimodal ultrasonic motor stator

The magnetic field tuning characteristics of an ultrasonic motor (USM) stator are discussed. The stator consists of two piezoelectric ceramic transducer (PZT) plates and one sandwiched-in Terfenol-D plate. The dimensions of the stator are carefully adjusted to specifically discuss the influence of the magnetic field on the frequency difference between the longitudinal and bending modes of the stator. The frequency difference discussed in this paper is usually small and mainly caused by uneven materials, machining errors and changes in external conditions (temperature, pre-stress or load). The longitudinal and bending modes of the stator are simultaneously excited by an external electric field to generate the elliptic motion trajectories of the driving points. A direct current (DC) magnetic field is applied to decrease the difference between the two mode frequencies of the fabricated stator. In experiments, the dependences of the two mode frequencies and their difference on DC magnetic fields are all investigated. The experimental results indicate that the difference between the longitudinal and bending mode frequencies of the PZT/Terfenol-D/PZT composite stator can be tuned by changing the intensity of the external DC magnetic field.     

Sensorimotor self-learning model based on operant conditioning for two-wheeled robot

Traditional control methods of two-wheeled robot are usually model-based and require the robot’s precise mathematic model which is hard to get. A sensorimotor self-learning model named SMM TWR is presented in this paper to handle these problems. The model consists of seven elements: the discrete learning time set, the sensory state set, the motion set, the sensorimotor mapping, the state orientation unit, the learning mechanism and the model’s entropy. The learning mechanism for SMM TWR is designed based on the theory of operant conditioning (OC), and it adjusts the sensorimotor mapping at every learning step. This helps the robot to choose motions. The leaning direction of the mechanism is decided by the state orientation unit. Simulation results show that with the sensorimotor model designed, the robot is endowed the abilities of self-learning and self-organizing, and it can learn the skills to keep itself balance through interacting with the environment.