數字孿生驅動(dòng)的長(cháng)距離帶式輸送機運行優(yōu)化方法

楊春雨; 卜令超; 陳斌

doi:10.16383/j.aas.c210979

數字孿生驅動(dòng)的長(cháng)距離帶式輸送機運行優(yōu)化方法

doi: 10.16383/j.aas.c210979 cstr: 32138.14.j.aas.c210979

1.
中國礦業(yè)大學(xué)信息與控制工程學(xué)院徐州 221116

基金項目: 國家自然科學(xué)基金(61873272, 62073327), 江蘇省自然科學(xué)基金(BK20200086, BK20200631)資助

詳細信息

作者簡(jiǎn)介:
楊春雨：中國礦業(yè)大學(xué)信息與控制工程學(xué)院教授. 2009年獲得東北大學(xué)博士學(xué)位. 主要研究方向為智能系統與先進(jìn)控制. 本文通信作者. E-mail: chunyuyang@cumt.edu.cn

卜令超：中國礦業(yè)大學(xué)信息與控制工程學(xué)院碩士研究生. 主要研究方向為系統建模與控制. E-mail: lingchaobu@cumt.edu.cn

陳斌：中國礦業(yè)大學(xué)信息與控制工程學(xué)院碩士研究生. 主要研究方向為模型預測控制, 分布式優(yōu)化控制. E-mail: chenbincumt@cumt.edu.cn

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- 文章訪(fǎng)問(wèn)數: 835
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出版歷程
- 收稿日期: 2021-10-16
- 錄用日期: 2022-02-10
- 網(wǎng)絡(luò )出版日期: 2022-05-05
- 刊出日期: 2024-11-26

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 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: 長(cháng)距離帶式輸送機是礦山、港口等領(lǐng)域運輸散裝物料的主要工具. 針對長(cháng)距離帶式輸送機的安全節能運行問(wèn)題, 研究數字孿生驅動(dòng)的運行優(yōu)化方法. 首先, 構建由數字孿生模型、模型同步算法、控制策略和現實(shí)帶式輸送機組成的數字孿生驅動(dòng)運行優(yōu)化框架; 然后, 建立數字孿生模型, 包括基于變質(zhì)量牛頓第二定律和有限元分析法的輸送帶動(dòng)力學(xué)模型、物料流動(dòng)態(tài)模型和動(dòng)態(tài)能耗模型; 最后, 提出數字孿生驅動(dòng)的計算決策?仿真評估?優(yōu)化校正(Decision-simulation-correction, DSC)優(yōu)化決策方法, 優(yōu)化帶式輸送機的穩態(tài)和暫態(tài)運行帶速, 形成可行帶速設定曲線(xiàn). 實(shí)驗結果表明, 數字孿生驅動(dòng)的帶式輸送機運行優(yōu)化方法可以實(shí)現帶式輸送機安全節能運行. 與傳統控制方法相比, 能夠根據運行工況實(shí)時(shí)調速, 提高輸送帶填充率, 節能13.87%.
- 長(cháng)距離帶式輸送機 /
- 數字孿生 /
- 運行優(yōu)化 /
- 動(dòng)態(tài)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 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%.
- Long distance belt conveyor /
- digital twin /
- operation optimization /
- dynamic model

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圖 1 傳統控制與數字孿生驅動(dòng)的優(yōu)化控制模式

Fig. 1 The modes of traditional control and optimization control driven by digital twin

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圖 2 帶式輸送機數字孿生驅動(dòng)運行優(yōu)化框架

Fig. 2 Framework for operation optimization of belt conveyor driven by digital twin

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圖 3 帶式輸送機有限元模型

Fig. 3 The finite element model of belt conveyor

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圖 4 基于數字孿生的DSC優(yōu)化策略

Fig. 4 DSC optimization strategy based on digital twin

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圖 5 變速曲線(xiàn)

Fig. 5 The curve of variable speed

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圖 6 變速策略

Fig. 6 The strategy of variable speed

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圖 7 張力示意圖

Fig. 7 The label of tension

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圖 8 半實(shí)物仿真實(shí)驗平臺

Fig. 8 Hardware-in-the-loop simulation platform

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圖 9 各微元段帶速(本文方法)

Fig. 9 The velocity of each segment (by the proposed method)

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圖 10 運行加速度

Fig. 10 Operating acceleration

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圖 11 緊側張力(本文方法)

Fig. 11 Tight-side tension (by the proposed method)

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圖 12 驅動(dòng)滾筒處張力

Fig. 12 The tension at the drive pulley

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圖 13 驅動(dòng)滾筒處張力瞬時(shí)變化(本文方法校正前)

Fig. 13 Instantaneous variation of tension at driving drum (by the proposed method without correction part)

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圖 14 物料流三維圖

Fig. 14 3D map of material flow

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圖 15 運載物料最大平均質(zhì)量(本文方法)

Fig. 15 The maximum average quality of carrying material (by the proposed method)

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圖 16 驅動(dòng)滾筒處張力瞬時(shí)變化(本文方法校正后)

Fig. 16 Instantaneous variation of tension at the drive pulley (by the proposed method with correction part)

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圖 17 運載物料最大平均質(zhì)量(定速方法)

Fig. 17 The maximum average quality of carrying material (by the method for constant speed)

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圖 18 各微元段帶速(定速方法)

Fig. 18 The velocity of each segment (by the method for constant speed)

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圖 19 緊側張力(定速方法)

Fig. 19 Tight-side tension (by the method for constant speed)

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圖 20 驅動(dòng)滾筒處張力瞬時(shí)變化(定速方法)

Fig. 20 Instantaneous variation of tension at the drive pulley (by the method for constant speed)

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圖 21 輸送帶填充率

Fig. 21 The filling rate of conveyor belt

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圖 22 能耗功率

Fig. 22 The energy consumption power

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表 1 輸送帶動(dòng)力學(xué)模型符號意義

Table 1 The significance of the symbols of the conveyor belt dynamic model

符號	含義(單位)	符號	含義(單位)
c_i	第 i 個(gè)微元段的等效黏性系數(N·s/m)	q(i, m)	m時(shí)刻輸送帶上 i 位置平均物質(zhì)量(kg/m)
c_t	張緊裝置微元段的等效黏性系數(N·s/m)	q_B	每米輸送帶的質(zhì)量(kg/m)
F_d	驅動(dòng)電機作用在驅動(dòng)滾筒上的驅動(dòng)力(N)	q_RO	每米承載側托輥平均質(zhì)量(kg/m)
F_i	第 i 個(gè)微元段承受的外力和(N)	q_RU	每米返回側托輥平均質(zhì)量(kg/m)
f_i	第 i 個(gè)微元段所受摩擦力(N)	s_i	第 i 個(gè)微元段的位置(m)
f_t	張緊裝置微元段所受摩擦力(N)	$ {{\dot s}_i}$	第 i 個(gè)微元段的速度(m/s)
g	重力加速度(m/s²)	$ {{\ddot s}_i}$	第 i 個(gè)微元段的加速度(m/s²)
k_i	第 i 個(gè)微元段的等效彈性系數(N/m)	$\Delta L_{{\rm{RO}}} $	承載側微元段的長(cháng)度(m)
k_t	張緊裝置微元段的等效彈性系數(N/m)	$\Delta L_{{\rm{RU}}} $	返回側微元段的長(cháng)度(m)
m_i	第 i 個(gè)微元段的等效質(zhì)量(kg)	μ	運載物料與輸送帶之間的摩擦系數
m_t	張緊裝置微元段的等效質(zhì)量(kg)

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表 2 帶式輸送機參數值

Table 2 The parameters value of belt conveyor

符號	數值	符號	數值
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	$\alpha $	180°
q_B	18.73 kg/m	μ₁	0.35
q_RO	15.75 kg/m

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表 3 迭代優(yōu)化過(guò)程

Table 3 The process of iterative optimization

迭代次數	變速次數	Dt (s)	a_max (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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