唐钢第二炼铁厂3#高炉开口机改造及效果

对唐钢第二炼铁厂3#高炉开口机的工作原理及其在工作中存在的问题进行了分析，通过对开口机四连杆机构、十路接头油管的改造，节约了大量的备件费用，具有较好的推广使用价值。     

从76届SEG年会看综合物化探技术的发展方向

文中在介绍76届SEG年会的展商、展台及会场专题报告与论文发布情况的基础上，阐述了参加本届SEG年会的体会，指出了重磁电技术发展的四个趋势：向海洋勘探技术方向发展、向复杂区综合勘探技术方向发展、向三维联合处理和三维可视化解释技术发展、向直接圈定和检测油气方向发展。     

Analysis of frictional energy dissipation on an annular surface with harmonic loading

Metallic mating surfaces in structural joints offer a good source of frictional energy dissipation resulting in a damped dynamic structural response. This paper reports the results of experiments where the energy dissipation per cycle occurring at a preloaded flat metallic annular interface subjected to cyclic tangential forces is measured. The effects of certain pertinent joint variables on this frictional energy dissipation are investigated by the application of Response Surface Methodology. A central composite rotatable design was utilized for developing empirical expressions for energy loss. The methodology presented suggests a useful technique for tribological research.     

基于专家系统的机器人高层规划

本文介绍一个基于专家系统的机器人高层规划系统,阐述几个潜在应用子系统,并应用专家系统方法进行多机器人协调避碰运动规划。本系统具有良好的规划性能。     

Development and implementation of a NURBS curve motion interpolator

This paper deals with the issues of development and implementation of a real-time NURBS interpolator for a six-axis robot. Using an open-architecture controller system as a testbed, a real-time NURBS curve interpolator was developed, implemented and tested. Sample runs were conducted with the resulting trajectories measured in real-time during robot motion. The resulting trajectories are analyzed, discussed and compared with those from a commonly used point-to-point approximation technique. The real-time NURBS curve interpolator's feasibility, advantages and related issues are also discussed.     

煤气管道膨胀节腐蚀和在线包焊技术应用

简单分析了高炉煤气中Cl元素的存在对不锈钢膨胀节的应力腐蚀问题和防止途径，作为一种临时性的防范措施，简要介绍了煤气膨胀节包焊实施步骤和措施。     

工业机器人解释器语义分析研究

介绍了语义分析的发展现状。针对目前解释器语义分析效率较低的问题,并结合工业机器人控制系统的特点,研究了利用语法分析栈来实现工业机器人解释器语义分析的方法,并实现了工业机器人编程语言IRL的语义分析。基于该方法的解释器在Visual Studio2005平台上用C＋＋实现,生成的目标代码运行于WinCE嵌入式系统。实验结果证明了该方法的正确性和高效性。     

Robots positioning control revisited

Positioning control systems for robot arms are presented within a general framework in view of unification and classification. Treating coupling torques from other links as an external disturbance reduces the design of the control system to that of SISO servomechanisms driving each of the robot axes individually. A short survey of many control strategies proposed in the literature presents them as different methods aiming at attenuation of this disturbance. The use of disturbance observers is shown to provide a nice and simple way for that purpose. This could be applied to the improvement of actual industrial robots at the cost of slight software modifications.     

Improving human robot collaboration through Force/Torque based learning for object manipulation

Human–Robot Collaboration (HRC) is a term used to describe tasks in which robots and humans work together to achieve a goal. Unlike traditional industrial robots, collaborative robots need to be adaptive; able to alter their approach to better suit the situation and the needs of the human partner. As traditional programming techniques can struggle with the complexity required, an emerging approach is to learn a skill by observing human demonstration and imitating the motions; commonly known as Learning from Demonstration (LfD). In this work, we present a LfD methodology that combines an ensemble machine learning algorithm (i.e. Random Forest (RF)) with stochastic regression, using haptic information captured from human demonstration. The capabilities of the proposed method are evaluated using two collaborative tasks; co-manipulation of an object (where the human provides the guidance but the robot handles the objects weight) and collaborative assembly of simple interlocking parts. The proposed method is shown to be capable of imitation learning; interpreting human actions and producing equivalent robot motion across a diverse range of initial and final conditions. After verifying that ensemble machine learning can be utilised for real robotics problems, we propose a further extension utilising Weighted Random Forest (WRF) that attaches weights to each tree based on its performance. It is then shown that the WRF approach outperforms RF in HRC tasks.