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.     

Approximate method for reliability assessment of complex phased mission systems

Phased-mission systems (PMSs) have wide applications in engineering practices, such as manmade satellites. Certain critical parts in the system, such as cold standby, hot standby and functional standby, are designed in redundancy architecture to achieve high reliability performance. State-space models such as Markov process have been used extensively in previous studies for reliability evaluation of PMSs with dynamic behaviors. The most popular way to deal with the dynamic behaviors is Markov process, but it is well known that Markov process is limited to exponential distribution. In practice, however, the lifetime of most machinery products can follow non-exponential distributions like the Weibull distribution which cannot be handled by the Markov process. In order to solve this kind of problem, we present a semi-Markov model combined with an approximation algorithm to analyze PMS reliability subjected to non-exponential failures. Furthermore, the accuracy of the approximation algorithm is investigated by comparing to an accurate solution, and a typical PMS (attitude and orbit control system) is analyzed to demonstrate the implementation of the method.     

城市道路水泥稳定碎石基层的施工与质量控制

水泥稳定层作为城市道路基层,是一种很好的结构材料。通过工程实践,讨论了水泥稳定碎石从材料的选用、拌和、运输、摊铺、碾压和养生等各个环节的施工技术问题及质量控制。     

级配对粗粒土直剪过程中抗剪强度与变形的影响研究

为了分析级配对粗粒土直剪过程中抗剪强度和变形的影响,开展不同级配试样的室内直剪试验,并根据试验结果标定细观参数,建立粗粒土数值直剪试验模型。从宏观和细观的角度探讨级配对粗粒土强度和变形的影响。结果表明:有效粒径、中值粒径和限制粒径相差不大时,空隙填充密实,结构性好,能够承受较大外力;粗颗粒含量多,颗粒间的挤压摩擦更剧烈,强力链增多;细颗粒含量越多,颗粒间孔隙填充不均匀,更易产生压缩变形,位移场越密集;空隙率随曲率系数、不均匀系数的增加先增大后减小。     

基于CVT的混联式电动汽车动力切换平稳性研究

针对四轮驱动越野车提出了一种基于金属带式无级自动变速器(CVT)的混联式结构,其动力切换平稳性是这种混联式电动汽车必须解决的关键技术之一。通过发动机、电机、离合器和CVT的协调控制可以使系统在驾驶员发出加速命令时快速响应以及在模式切换时平稳,这将保证驾驶员在车辆切换过程中没有异常感觉。     

关于轮胎吊接地问题的探讨

上海港外高桥港区进行轮胎式集装箱起重机驱动油改电项目,产生了用何种方法接地问题。对供电铁塔到RTG(Rubber-Tired Container Gantry Crane)处接地问题进行探讨。通过计算,找出了合适的接地模式,既能保障人身安全,又能让设备正常运行。     

突发大规模需求下铁路军事运输保障研究

以"5·12"汶川地震为背景,分析了突发大规模需求下铁路军事运输保障的特点及要求,提出了应急铁路军事运输保障的具体对策,如建立健全铁路军事运输指挥机制、制订输送保障运行计划等,对铁路军事运输部门提高突发大规模需求情况下的运输保障能力具有借鉴意义.     

基于统计和有限元分析的裂纹敏感区确定方法

港口机械正在向大型、高速、重载方向发展,其金属结构的质量越来越大,它的缺陷会给机械工作带来隐患,而且一旦出现断臂等重大事故,将造成巨大危害[1].     

基于层次分析法的拉萨市交通安全评价模型研究

随着拉萨市经济水平的发展,城市道路交通安全变成了人们较为重视的社会问题.为改善道路交通安全现状,本文将从人为、车辆、道路和环境四个评价指标,采用层次分析法构建交通安全评价模型,对拉萨市交通安全进行评价分析,为城市道路交通安全提供参考依据.     

激光探测与测量视觉技术在堆取料机全自动控制中的应用

针对散货料场堆取料机人工操作堆取作业随意性大、精度差、效率低等现状,设计了一种堆取料机全自动控制系统。该系统基于激光雷达(Lidar)机器视觉技术,通过3D激光扫描仪实时获取料堆形状的点云数据,并完成对目标料堆的在线实时建模,最后控制堆取料机完成自动作业;提出了一种基于视觉图像处理算法的作业路径规划算法,通过实时提前预测作业轨迹来指导堆取料机自动作业。实践表明该控制系统提高了设备的作业效率,降低了作业成本。