The multi-crawler travelling gears are used to carry and move the giant mining equipment, the controllability of their trajectories are directly influence the security and exploitation efficiency of the mine productions. The turning of the multi-crawler travelling gears is accomplished by rotating the steer crawler to a certain angle, and utilizing the lateral force from ground acting on the steer crawler to overcome the steering resistance, so that the controllability of steering trajectory is lack of accuracy, and the track link and the track wheel would be worn severely. In order to solve this serious problem of the multi-crawler travelling gears, this project will research on the mechanism of adaptive driving and the related key technologies by putting forward an unbalanced drive pattern as a base which combines the control of crawler speed and its deflection angle. Firstly, an electromechanical coupling dynamic model will be constructed based on which parameters of driving and steering system will be optimally matched. In addition, this model will contribute to the route planning of the multi-crawler driving gears to ensure the high stability and low power consumption. Secondly, for the purpose of tracking the planned route effectively and precisely, fuzzy inference rules will be taken into account to develop the adaptive driving control system which heavily based on the match scheme of parameters of driving and steering system. Eventually, the performance of the adaptive control system will be verified by co-simulation between the virtual prototype of multi-crawler travelling gears and the model of control system. Meanwhile, a physical prototype will be applied to field tests to validate the practicality and reliability of the adaptive driving system. The research of this project will enrich the design and the control theory of the multi-crawler travelling gears, and also have significance for improving the intelligent level of the heavy mining equipment and constructing the unmanned open pit mine.
多履带行走装置担负着大型采矿装备的承载和行驶,其行走轨迹的可控性直接影响矿山生产的安全性和开采效率。多履带行走装置通过将转向履带偏转一定角度,利用地面对转向履带的侧向力克服转向阻力的转向方式导致转向轨迹可控性差、履带链和支重轮磨损严重。本项目提出多履带行走装置的非均衡独立驱动模式,联合差速法和偏转法实现协同转向控制,并基于此开展多履带行走装置自适应行走机理及关键技术研究。首先建立多履带行走装置机电耦合动力学模型,优化不同条件下履带驱动和转向系统参数的匹配方案;提出考虑转向稳定性及能耗的多履带行走装置路径规划方法,并以参数匹配方案为基础,利用模糊推理规则开发其自适应行走控制系统,使其精确高效地跟踪规划路径;通过虚拟样机及自适应控制系统联合仿真验证多履带自适应行驶系统的性能并通过物理样机试验验证其实用性和可靠性。本课题对完善多履带行走装置设计和控制理论,提升重矿装备智能化水平具有重要意义。
多履带机械机电耦合设计方法及其自适应行驶控制技术是重型采矿装备智能化发展急需解决的关键课题。本项目基于多履带行走装置的结构特点和运动特性,建立了多履带机械典型工况行驶动力学模型,结合履带驱动电机的动态特性,建立了多履带机械机电耦合动力学模型,并给出了相应的数值求解方法,计算了多履带机械典型行驶工况下机电参数的变化规律,分析多履带机械的结构参数和驱动状态对行驶性能的影响,通过对四履带物理样机试验和六履带斗轮挖掘机电机功率的试验测试,验证了理论模型和分析结果的正确。开发了多履带机械行驶性能分析平台,实现对多履带机械典型行驶工况机电性能参数的计算和评价,该平台可分析不同履带布置方式、履带驱动形式对多履带机械转向特性的影响,优化不同条件下履带驱动和转向系统参数的匹配方案,实现准确转向。将A*算法与RRT*算法相结合,提出一种适合多履带大型装备的路径规划方法,即满足远距离行走时的避障要求,同时满足短距离调姿的路径光滑性要求;基于卫星定位信息对多履带机械的导航控制系统进行了设计,以六履带机械为例,将实际行驶路径与预设路径之间的距离偏差和航向角偏差作为输入变量,采用模糊PID控制方法,通过控制转向履带组偏转角度和多履带机械各条履带行驶速度来调整车辆的位置和姿态,从而实现其导航控制。建立了数字化功能样机模型和基于RTK-GPS导航控制试验平台,分别进行了数字化功能样机联合仿真和多履带物理样机试验研究,验证了本课题所设计多履带机械卫星导航控制系统的控制效果和实用性,在此基础上,开发了基于RTK-GPS和预瞄-模糊控制的无人电铲轨迹跟踪导航系统,应用于无人操纵矿用挖掘机,轨迹误差达到厘米级。依托本项目发表学术论文21篇,其中SCI收录18篇,出版专著1部,申报发明专利7项,已授权2项,培养研究生11名,其中4人获得博士学位,7人获得硕士学位。本项目提出的多履带机械机电耦合设计理论和自适应行驶技术,为重型履带装备无人化和智能化提供了基础。
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数据更新时间:2023-05-31
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