An Operation Optimization Method for Long Distance Belt Conveyors Driven by Digital Twin
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摘要: 长距离带式输送机是矿山、港口等领域运输散装物料的主要工具. 针对长距离带式输送机的安全节能运行问题, 研究数字孪生驱动的运行优化方法. 首先, 构建由数字孪生模型、模型同步算法、控制策略和现实带式输送机组成的数字孪生驱动运行优化框架; 然后, 建立数字孪生模型, 包括基于变质量牛顿第二定律和有限元分析法的输送带动力学模型、物料流动态模型和动态能耗模型; 最后, 提出数字孪生驱动的计算决策−仿真评估−优化校正(Decision-simulation-correction, DSC)优化决策方法, 优化带式输送机的稳态和暂态运行带速, 形成可行带速设定曲线. 实验结果表明, 数字孪生驱动的带式输送机运行优化方法可以实现带式输送机安全节能运行. 与传统控制方法相比, 能够根据运行工况实时调速, 提高输送带填充率, 节能13.87%.Abstract: Long distance belt conveyors are used as a main tool for transporting bulk materials in the fields of mines, ports and so on. For the safe and energy saving operation of long distance belt conveyors, the operation optimization method driven by digital twin is studied. Firstly, the framework of the operation optimization driven by digital twin is constructed, which includes digital twin models, model synchronization algorithms, control strategy, and realistic belt conveyors. Then, digital twin models are established, including the dynamic model of conveyor belt based on the variable quality Newton＇s second law and finite element analysis method, material flow dynamic model and dynamic energy model. Finally, the decision-simulation-correction (DSC) optimization method driven by digital twin is proposed, which can optimize the steady and transient belt speed of the belt conveyor to build a feasible speed setting curve. Experiments show that the operation optimization method driven by digital twin can result in a belt conveyor that is both safe and energy efficient. Compared with the traditional method, the proposed method can adjust the belt speed setpoint in real-time based on operating conditions, increasing the conveyor belt fill rate, which results in energy savings of 13.87%.
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Key words:
- Long distance belt conveyor /
- digital twin /
- operation optimization /
- dynamic model
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图 1 传统控制与数字孪生驱动的优化控制模式
Fig. 1 The modes of traditional control and optimization control driven by digital twin
图 2 带式输送机数字孪生驱动运行优化框架
Fig. 2 Framework for operation optimization of belt conveyor driven by digital twin
图 13 驱动滚筒处张力瞬时变化(本文方法校正前)
Fig. 13 Instantaneous variation of tension at driving drum (by the proposed method without correction part)
图 15 运载物料最大平均质量(本文方法)
Fig. 15 The maximum average quality of carrying material (by the proposed method)
图 16 驱动滚筒处张力瞬时变化(本文方法校正后)
Fig. 16 Instantaneous variation of tension at the drive pulley (by the proposed method with correction part)
图 17 运载物料最大平均质量(定速方法)
Fig. 17 The maximum average quality of carrying material (by the method for constant speed)
图 18 各微元段带速(定速方法)
Fig. 18 The velocity of each segment (by the method for constant speed)
图 20 驱动滚筒处张力瞬时变化(定速方法)
Fig. 20 Instantaneous variation of tension at the drive pulley (by the method for constant speed)
表 1 输送带动力学模型符号意义
Table 1 The significance of the symbols of the conveyor belt dynamic model
符号 含义(单位) 符号 含义(单位) ci 第 i 个微元段的等效黏性系数(N·s/m) q(i, m) m时刻输送带上 i 位置平均物质量(kg/m) ct 张紧装置微元段的等效黏性系数(N·s/m) qB 每米输送带的质量(kg/m) Fd 驱动电机作用在驱动滚筒上的驱动力(N) qRO 每米承载侧托辊平均质量(kg/m) Fi 第 i 个微元段承受的外力和(N) qRU 每米返回侧托辊平均质量(kg/m) fi 第 i 个微元段所受摩擦力(N) si 第 i 个微元段的位置(m) ft 张紧装置微元段所受摩擦力(N) $ {{\dot s}_i}$ 第 i 个微元段的速度(m/s) g 重力加速度(m/s2) $ {{\ddot s}_i}$ 第 i 个微元段的加速度(m/s2) ki 第 i 个微元段的等效弹性系数(N/m) $\Delta L_{{\rm{RO}}} $ 承载侧微元段的长度(m) kt 张紧装置微元段的等效弹性系数(N/m) $\Delta L_{{\rm{RU}}} $ 返回侧微元段的长度(m) mi 第 i 个微元段的等效质量(kg) μ 运载物料与输送带之间的摩擦系数 mt 张紧装置微元段的等效质量(kg) 
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表 2 带式输送机参数值
Table 2 The parameters value of belt conveyor
符号 数值 符号 数值 C 1.336 qRU 7.76 kg/m f 0.024 Qmax 176.37 kg/m g 9.8 m/s2 SA, min 5.4 L 313.25 m SB, min 8 mt 4000 kg$\alpha $ 180° qB 18.73 kg/m μ1 0.35 qRO 15.75 kg/m
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表 3 迭代优化过程
Table 3 The process of iterative optimization
迭代次数 变速次数 Dt (s) amax (m·s−2) ${F_{ { { {\rm{T} }1} } } }\;({\rm{kN} })$ ${F_{ { { {\rm{Tr} } } } } }\;({\rm{kN} })$ $\Delta {F_{ { { {\rm{Tr} } } } } }\;({\rm{kN} })$ ${\bar q}\; ({\rm{kg} } \cdot{\rm{ } }m^{−1})$ 0 1 17 0.291 41.97 17.47 4.69 0 2 6 −0.275 60.86 36.36 11.39 176.19 3 4 0.223 45.10 20.60 15.04 176.10 4 4 −0.279 65.96 41.46 17.88 176.12 1 1 17 0.291 41.97 17.47 4.69 0 2 8 −0.212 55.27 30.77 6.47 176.19 3 7 0.140 42.84 18.34 4.07 176.10 4 7 −0.176 52.42 27.92 6.05 176.12
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