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              數字孿生驅動的長距離帶式輸送機運行優化方法

              楊春雨 卜令超 陳斌

              楊春雨, 卜令超, 陳斌. 數字孿生驅動的長距離帶式輸送機運行優化方法. 自動化學報, 2023, 49(9): 1?15 doi: 10.16383/j.aas.c210979
              引用本文: 楊春雨, 卜令超, 陳斌. 數字孿生驅動的長距離帶式輸送機運行優化方法. 自動化學報, 2023, 49(9): 1?15 doi: 10.16383/j.aas.c210979
              Yang Chun-Yu, Bu Ling-Chao, Chen Bin. An operation optimization method for long distance belt conveyors driven by digital twin. Acta Automatica Sinica, 2023, 49(9): 1?15 doi: 10.16383/j.aas.c210979
              Citation: Yang Chun-Yu, Bu Ling-Chao, Chen Bin. An operation optimization method for long distance belt conveyors driven by digital twin. Acta Automatica Sinica, 2023, 49(9): 1?15 doi: 10.16383/j.aas.c210979

              數字孿生驅動的長距離帶式輸送機運行優化方法

              doi: 10.16383/j.aas.c210979
              基金項目: 國家自然科學基金(61873272, 62073327), 江蘇省自然科學基金(BK20200086, BK20200631)資助
              詳細信息
                作者簡介:

                楊春雨:中國礦業大學信息與控制工程學院教授. 2009年獲得東北大學博士學位. 主要研究方向為智能系統與先進控制. 本文通信作者. E-mail: chunyuyang@cumt.edu.cn

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

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

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

              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: 長距離帶式輸送機是礦山、港口等領域運輸散裝物料的主要工具. 針對長距離帶式輸送機的安全節能運行問題, 研究數字孿生驅動的運行優化方法. 首先, 構建由數字孿生模型、模型同步算法、控制策略和現實帶式輸送機組成的數字孿生驅動運行優化框架; 然后, 建立數字孿生模型, 包括基于變質量牛頓第二定律和有限元分析法的輸送帶動力學模型、物料流動態模型和動態能耗模型; 最后, 提出數字孿生驅動的計算決策?仿真評估?優化校正(Decision-simulation-correction, DSC)優化決策方法, 優化帶式輸送機的穩態和暫態運行帶速, 形成可行帶速設定曲線. 實驗結果表明, 數字孿生驅動的帶式輸送機運行優化方法可以實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時調速, 提高輸送帶填充率, 節能13.87%.
              • 圖  1  傳統控制與數字孿生驅動的優化控制模式

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

                圖  2  帶式輸送機數字孿生驅動運行優化框架

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

                圖  3  帶式輸送機有限元模型

                Fig.  3  The finite element model of belt conveyor

                圖  4  基于數字孿生的DSC優化策略

                Fig.  4  DSC optimization strategy based on digital twin

                圖  5  變速曲線

                Fig.  5  The curve of variable speed

                圖  6  變速策略

                Fig.  6  The strategy of variable speed

                圖  7  張力示意圖

                Fig.  7  The label of tension

                圖  8  半實物仿真實驗平臺

                Fig.  8  Digital twin system simulation experiment platform

                圖  9  各段微元帶速

                Fig.  9  The velocity of each segment

                圖  10  運行加速度

                Fig.  10  Operating acceleration

                圖  11  緊側張力

                Fig.  11  Tight-side tension at the drive pulley

                圖  12  驅動滾筒處張力

                Fig.  12  The tension at the drive pulley

                圖  13  驅動滾筒處張力瞬時變化

                Fig.  13  Instantaneous variation of tension at driving drum

                圖  14  物料流三維圖

                Fig.  14  3D map of material flow

                圖  15  運載物料最大平均質量

                Fig.  15  The maximum average quality of carrying material

                圖  16  驅動滾筒處張力瞬時變化

                Fig.  16  Instantaneous variation of tension at the drive pulley

                圖  17  運載物料最大平均質量

                Fig.  17  The maximum average quality of carrying material

                圖  18  各段微元帶速

                Fig.  18  The velocity of each segment

                圖  19  緊側張力

                Fig.  19  Tight-side tension at the drive pulley

                圖  20  驅動滾筒處張力瞬時變化

                Fig.  20  Instantaneous variation of tension atthe drive pulley

                圖  21  輸送帶填充率

                Fig.  21  The filling rate of conveyor belt

                圖  22  能耗功率

                Fig.  22  The energy consumption power

                表  1  輸送帶動力學模型符號意義

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

                符號 意義 符號 意義
                ci i 個微元段的等效粘性系數(N·(s/m)) q (i, m) m時刻輸送帶上 i 位置平均物質量(kg/m)
                ct 張緊裝置微元段的等效粘性系數(N·(s/m)) qB 每米輸送帶的質量(kg/m)
                Fd 驅動電機作用在驅動滾筒上的驅動力(N) qRO 每米承載側托輥平均質量(kg/m)
                Fi i 個微元段承受的外力和(N) qRU 每米返回側托輥平均質量(kg/m)
                fi i 個微元段所受摩擦力(N) si i 個微元段的位置(m)
                ft 張緊裝置微元段所受摩擦力(N) $ {{\dot s}_i}$ i 個微元段的速度(m/s)
                g 重力加速度(m/s)2 $ {{\ddot s}_i}$ i 個微元段的加速度(m/s)2
                ki i 個微元段的等效彈性系數(N/m) ΔLRO 承載側微元段的長度(m)
                kt 張緊裝置微元段的等效彈性系數(N/m) ΔLRU 返回側微元段的長度(m)
                mi i 個微元段的等效質量(kg) μ 運載物料與輸送帶之間的摩擦系數
                mt 張緊裝置微元段的等效質量(kg)
                下載: 導出CSV

                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
                C1.336qRU7.76 (kg/m)
                f0.024Qmax176.37 (kg/m)
                g9.8 (m/s2)SA,min5.4
                L313.25 mSB,min8
                mt4000 kgα180°
                qB18.73 (kg/m)μ10.35
                qRO15.75 (kg/m)
                下載: 導出CSV

                表  3  迭代優化過程

                Table  3  The process of iterative optimization

                迭代次數 變速次數 Dt (s) amax (m·s?2) FT1 (kN) FTr (kN) ΔFTr (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
                下載: 導出CSV
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