数字孪生驱动的长距离带式输送机运行优化方法

杨春雨; 卜令超; 陈斌

doi:10.16383/j.aas.c210979

数字孪生驱动的长距离带式输送机运行优化方法

doi: 10.16383/j.aas.c210979

1.
中国矿业大学信息与控制工程学院徐州 221116

基金项目: 国家自然科学基金(61873272, 62073327), 江苏省自然科学基金(BK20200086, BK20200631)资助

详细信息

作者简介:
杨春雨：中国矿业大学信息与控制工程学院教授. 2009年获得东北大学博士学位. 主要研究方向为智能系统与先进控制. 本文通信作者. E-mail: chunyuyang@cumt.edu.cn

卜令超：中国矿业大学信息与控制工程学院硕士研究生. 主要研究方向为系统建模与控制. E-mail: lingchaobu@cumt.edu.cn

陈斌：中国矿业大学信息与控制工程学院硕士研究生. 主要研究方向为模型预测控制, 分布式优化控制. E-mail: chenbincumt@cumt.edu.cn

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出版历程
- 收稿日期: 2021-10-16
- 录用日期: 2022-02-10
- 网络出版日期: 2022-05-05

An Operation Optimization Method for Long Distance Belt Conveyors Driven by Digital Twin

1.
School of Information and Control Engineering, China University of Mining and Technology, Xuzhou 221116

Funds: Supported by National Natural Science Foundation of China (61873272, 62073327) and National Natural Science Foundation of Jiangsu Province (BK20200086, BK20200631)

More Information

Author Bio:
YANG Chun-Yu　Professor at the School of Information and Control Engineering, China University of Mining and Technology. He received his Ph.D. degree from Northeastern University in 2009. His research interest covers intelligent system and advanced control. Corresponding author of this paper

BU Ling-Chao　Master student at the School of Information and Control Engineering, China University of Mining and Technology. His main research interest is system modeling and control

CHEN Bin　Master student at the School of Information and Control Engineering, China University of Mining and Technology. His research interest covers model predictive control and distributed optimal control

摘要

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%.
- 长距离带式输送机 /
- 数字孪生 /
- 运行优化 /
- 动态模型
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 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 control method, the proposed method can boost the conveyor belt fill rate while reducing energy usage by 13.87%.
- Long distance belt conveyors /
- 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 mode of traditional control and optimization control driven by digital twin

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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

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图 3 带式输送机有限元模型

Fig. 3 The finite element model of belt conveyor

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图 4 基于数字孪生的DSC优化策略

Fig. 4 DSC optimization strategy based on digital twin

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图 5 变速曲线

Fig. 5 The curve of variable speed

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图 6 变速策略

Fig. 6 The strategy of variable speed

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图 7 张力示意图

Fig. 7 The label of tension

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图 8 半实物仿真实验平台

Fig. 8 Digital twin system simulation experiment platform

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图 9 各段微元带速

Fig. 9 The velocity of each segment

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图 10 运行加速度

Fig. 10 Operating acceleration

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图 11 紧侧张力

Fig. 11 Tight-side tension at the drive pulley

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图 12 驱动滚筒处张力

Fig. 12 The tension at the drive pulley

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图 13 驱动滚筒处张力瞬时变化

Fig. 13 Instantaneous variation of tension at driving drum

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图 14 物料流三维图

Fig. 14 3D map of material flow

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图 15 运载物料最大平均质量

Fig. 15 The maximum average quality of carrying material

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图 16 驱动滚筒处张力瞬时变化

Fig. 16 Instantaneous variation of tension at the drive pulley

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图 17 运载物料最大平均质量

Fig. 17 The maximum average quality of carrying material

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图 18 各段微元带速

Fig. 18 The velocity of each segment

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图 19 紧侧张力

Fig. 19 Tight-side tension at the drive pulley

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图 20 驱动滚筒处张力瞬时变化

Fig. 20 Instantaneous variation of tension atthe drive pulley

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图 21 输送带填充率

Fig. 21 The filling rate of conveyor belt

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图 22 能耗功率

Fig. 22 The energy consumption power

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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	意义	符号	意义
c_i	第 i 个微元段的等效粘性系数(N·(s/m))	q (i, m)	m时刻输送带上 i 位置平均物质量(kg/m)
c_t	张紧装置微元段的等效粘性系数(N·(s/m))	q_B	每米输送带的质量(kg/m)
F_d	驱动电机作用在驱动滚筒上的驱动力(N)	q_RO	每米承载侧托辊平均质量(kg/m)
F_i	第 i 个微元段承受的外力和(N)	q_RU	每米返回侧托辊平均质量(kg/m)
f_i	第 i 个微元段所受摩擦力(N)	s_i	第 i 个微元段的位置(m)
f_t	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/s)²	$ {{\ddot s}_i}$	第 i 个微元段的加速度(m/s)²
k_i	第 i 个微元段的等效弹性系数(N/m)	ΔL_RO	承载侧微元段的长度(m)
k_t	张紧装置微元段的等效弹性系数(N/m)	ΔL_RU	返回侧微元段的长度(m)
m_i	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
m_t	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	q_RU	7.76 (kg/m)
f	0.024	Q_max	176.37 (kg/m)
g	9.8 (m/s²)	S_A,min	5.4
L	313.25 m	S_B,min	8
m_t	4000 kg	α	180°
q_B	18.73 (kg/m)	μ₁	0.35
q_RO	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)	a_max (m·s⁻²)	F_T1 (kN)	F_Tr (kN)	ΔF_Tr (kN)	$ {\bar q}$(kg·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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