The bucket wheel reclaimer(BWR) is a key piece of equipment which has been widely used for stacking and reclaiming bulk materials(i.e.iron ore and coal) in places such as ports,iron-steel plants,coal storage areas,and...The bucket wheel reclaimer(BWR) is a key piece of equipment which has been widely used for stacking and reclaiming bulk materials(i.e.iron ore and coal) in places such as ports,iron-steel plants,coal storage areas,and power stations from stockpiles.BWRs are very large in size,heavy in weight,expensive in price,and slow in motion.There are many challenges in attempting to automatically control their motion to accurately follow the required trajectories involving uncertain parameters from factors such as friction,turbulent wind,its own dynamics,and encoder limitations.As BWRs are always heavily engaged in production and cannot be spared very long for motion control studies and associated developments,a BWR model and simulation environment closely resembling real life conditions would be beneficial.The following research focused mainly on the implementation of fuzzy logic to a BWR motion control from an engineer's perspective.First,the modeling of a BWR including partially known parameters such as friction force and turbulence to the system was presented.This was then followed by the design of a fuzzy logic-based control built on a model-based control loop.The investigation provides engineers with an example of applying fuzzy logic in a model based approach to properly control the motion of a large BWR following defined trajectories,as well as to show possible ways of further improving the controller performance.The result indicates that fuzzy logic can be applied easily by engineers to overcome most motion control issues involving a large BWR.展开更多
Bucket wheel reclaimer(BWR)is an extremely complex engineering machine that involves multiple disciplines,such as structure,dynamics,and electromechanics.The conventional design strategy,namely,sequential strategy,is ...Bucket wheel reclaimer(BWR)is an extremely complex engineering machine that involves multiple disciplines,such as structure,dynamics,and electromechanics.The conventional design strategy,namely,sequential strategy,is structural design followed by control optimization.However,the global optimal solution is difficult to achieve because of the discoordination of structural and control parameters.The co-design strategy is explored to address the aforementioned problem by combining the structural and control system design based on simultaneous dynamic optimization approach.The radial basis function model is applied for the planning of the rotation speed considering the relationships of subsystems to minimize the energy consumption per volume.Co-design strategy is implemented to resolve the optimization problem,and numerical results are compared with those of sequential strategy.The dynamic response of the BWR is also analyzed with different optimization strategies to evaluate the advantages of the strategies.Results indicate that co-design strategy not only can reduce the energy consumption of the BWR but also can achieve a smaller vibration amplitude than the sequential strategy.展开更多
文中针对斗轮堆取料机中料斗在挖取料过程中的磨损问题,采用离散元法(Discrete Element Method,DEM)描述颗粒物料运动,并通过Archard磨损模型预测料斗壁面磨损情况,分析了颗粒物料对料斗切向和法向累积的接触力,基于EDEM软件开展了料斗...文中针对斗轮堆取料机中料斗在挖取料过程中的磨损问题,采用离散元法(Discrete Element Method,DEM)描述颗粒物料运动,并通过Archard磨损模型预测料斗壁面磨损情况,分析了颗粒物料对料斗切向和法向累积的接触力,基于EDEM软件开展了料斗尺寸参数对磨损影响规律的仿真试验研究。结果表明,Relative Wear模型能够较好地反映斗轮堆取料机料斗的磨损规律;料斗的磨损量随斗壁倒角的减小呈上升趋势,在普通料斗上增加倒角,能够显著减小料斗的磨损量;料斗切向收缩角的最优选择要与实际工况相结合,选出最优切向收缩角为4°;在径向收缩角2°~10°范围内,料斗的磨损量随径向收缩角的增大呈减小趋势。展开更多
基金support through the ARC Linkage LP0989780 grant titled "The study anddevelopment of a 3-D real-time stockpile management system"the support in part from Institute for Mineral and Energy Resources,University of Adelaide 2009-2010,as well as Faculty of Engineering,Computer and Mathematical Sciences strategic research funding,2010
文摘The bucket wheel reclaimer(BWR) is a key piece of equipment which has been widely used for stacking and reclaiming bulk materials(i.e.iron ore and coal) in places such as ports,iron-steel plants,coal storage areas,and power stations from stockpiles.BWRs are very large in size,heavy in weight,expensive in price,and slow in motion.There are many challenges in attempting to automatically control their motion to accurately follow the required trajectories involving uncertain parameters from factors such as friction,turbulent wind,its own dynamics,and encoder limitations.As BWRs are always heavily engaged in production and cannot be spared very long for motion control studies and associated developments,a BWR model and simulation environment closely resembling real life conditions would be beneficial.The following research focused mainly on the implementation of fuzzy logic to a BWR motion control from an engineer's perspective.First,the modeling of a BWR including partially known parameters such as friction force and turbulence to the system was presented.This was then followed by the design of a fuzzy logic-based control built on a model-based control loop.The investigation provides engineers with an example of applying fuzzy logic in a model based approach to properly control the motion of a large BWR following defined trajectories,as well as to show possible ways of further improving the controller performance.The result indicates that fuzzy logic can be applied easily by engineers to overcome most motion control issues involving a large BWR.
基金Supported by the National Key R&D Program of China(Grant Nos.2018YFB1700704 and 2018YFB1702502).
文摘Bucket wheel reclaimer(BWR)is an extremely complex engineering machine that involves multiple disciplines,such as structure,dynamics,and electromechanics.The conventional design strategy,namely,sequential strategy,is structural design followed by control optimization.However,the global optimal solution is difficult to achieve because of the discoordination of structural and control parameters.The co-design strategy is explored to address the aforementioned problem by combining the structural and control system design based on simultaneous dynamic optimization approach.The radial basis function model is applied for the planning of the rotation speed considering the relationships of subsystems to minimize the energy consumption per volume.Co-design strategy is implemented to resolve the optimization problem,and numerical results are compared with those of sequential strategy.The dynamic response of the BWR is also analyzed with different optimization strategies to evaluate the advantages of the strategies.Results indicate that co-design strategy not only can reduce the energy consumption of the BWR but also can achieve a smaller vibration amplitude than the sequential strategy.
文摘文中针对斗轮堆取料机中料斗在挖取料过程中的磨损问题,采用离散元法(Discrete Element Method,DEM)描述颗粒物料运动,并通过Archard磨损模型预测料斗壁面磨损情况,分析了颗粒物料对料斗切向和法向累积的接触力,基于EDEM软件开展了料斗尺寸参数对磨损影响规律的仿真试验研究。结果表明,Relative Wear模型能够较好地反映斗轮堆取料机料斗的磨损规律;料斗的磨损量随斗壁倒角的减小呈上升趋势,在普通料斗上增加倒角,能够显著减小料斗的磨损量;料斗切向收缩角的最优选择要与实际工况相结合,选出最优切向收缩角为4°;在径向收缩角2°~10°范围内,料斗的磨损量随径向收缩角的增大呈减小趋势。
