CN109100995B - 基于决策者偏好信息的铝电解节能减排优化方法 - Google Patents
基于决策者偏好信息的铝电解节能减排优化方法 Download PDFInfo
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- CN109100995B CN109100995B CN201810193062.7A CN201810193062A CN109100995B CN 109100995 B CN109100995 B CN 109100995B CN 201810193062 A CN201810193062 A CN 201810193062A CN 109100995 B CN109100995 B CN 109100995B
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- 229910052782 aluminium Inorganic materials 0.000 title claims abstract description 94
- XAGFODPZIPBFFR-UHFFFAOYSA-N aluminium Chemical compound [Al] XAGFODPZIPBFFR-UHFFFAOYSA-N 0.000 title claims abstract description 84
- 238000005868 electrolysis reaction Methods 0.000 title claims abstract description 49
- 238000000034 method Methods 0.000 title claims abstract description 38
- 238000005457 optimization Methods 0.000 title claims abstract description 20
- 238000004519 manufacturing process Methods 0.000 claims abstract description 47
- 239000002245 particle Substances 0.000 claims abstract description 45
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 23
- 238000005265 energy consumption Methods 0.000 claims abstract description 21
- 238000013528 artificial neural network Methods 0.000 claims abstract description 16
- 230000000306 recurrent effect Effects 0.000 claims abstract description 15
- 230000009467 reduction Effects 0.000 claims abstract description 9
- 150000001875 compounds Chemical class 0.000 claims abstract description 8
- 238000004134 energy conservation Methods 0.000 claims abstract description 7
- 230000006870 function Effects 0.000 claims description 51
- 210000002569 neuron Anatomy 0.000 claims description 41
- 210000004027 cell Anatomy 0.000 claims description 37
- 238000012549 training Methods 0.000 claims description 20
- -1 perfluoro compound Chemical class 0.000 claims description 14
- 238000012546 transfer Methods 0.000 claims description 14
- AZDRQVAHHNSJOQ-UHFFFAOYSA-N alumane Chemical compound [AlH3] AZDRQVAHHNSJOQ-UHFFFAOYSA-N 0.000 claims description 10
- 238000004364 calculation method Methods 0.000 claims description 4
- 239000003792 electrolyte Substances 0.000 claims description 3
- 230000007246 mechanism Effects 0.000 claims description 3
- 239000004744 fabric Substances 0.000 claims 1
- 230000008569 process Effects 0.000 abstract description 13
- 239000005431 greenhouse gas Substances 0.000 abstract description 3
- TXEYQDLBPFQVAA-UHFFFAOYSA-N tetrafluoromethane Chemical compound FC(F)(F)F TXEYQDLBPFQVAA-UHFFFAOYSA-N 0.000 description 5
- 230000008859 change Effects 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 239000004411 aluminium Substances 0.000 description 1
- 238000005094 computer simulation Methods 0.000 description 1
- 238000012937 correction Methods 0.000 description 1
- 230000008878 coupling Effects 0.000 description 1
- 238000010168 coupling process Methods 0.000 description 1
- 238000005859 coupling reaction Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000003912 environmental pollution Methods 0.000 description 1
- 238000009776 industrial production Methods 0.000 description 1
- 238000013507 mapping Methods 0.000 description 1
- 238000003062 neural network model Methods 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM]
- G05B19/41885—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM] characterised by modeling, simulation of the manufacturing system
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/32—Operator till task planning
- G05B2219/32339—Object oriented modeling, design, analysis, implementation, simulation language
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P80/00—Climate change mitigation technologies for sector-wide applications
- Y02P80/10—Efficient use of energy, e.g. using compressed air or pressurized fluid as energy carrier
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Abstract
Description
样本编号 | 1 | 2 | 3 | 4 | …… |
x<sub>1</sub> | 1683 | 1682 | 1686 | 1746 | …… |
x<sub>2</sub> | 624 | 716 | 625 | 743 | …… |
x<sub>3</sub> | 2.52 | 2.52 | 2.51 | 2.46 | …… |
x<sub>4</sub> | 1234 | 1230 | 1234 | 1235 | …… |
x<sub>5</sub> | 18.5 | 16.5 | 17.5 | 20 | …… |
x<sub>6</sub> | 14 | 14 | 15 | 16 | …… |
x<sub>7</sub> | 942 | 938 | 946 | 942 | …… |
y<sub>1</sub> | 94.65 | 94.66 | 94.43 | 93.22 | …… |
y<sub>2</sub> | 3721 | 3720 | 3725 | 3717 | …… |
y<sub>3</sub> | 4.25 | 4.84 | 4.01 | 4.15 | …… |
y<sub>4</sub> | 12354.3 | 12316.4 | 12283.1 | 12747.2 | …… |
目标函数 | 电流效率 | 槽电压 | 全氟化物排放量 | 吨铝能耗 |
迭代次数 | 1000 | 1000 | 1000 | 1000 |
隐含层传递函数 | Tansig | Logsig | Logsig | Tansig |
输出层传递函数 | Purelin | Purlin | Purelin | Purelin |
隐含层节点数 | 13 | 12 | 12 | 13 |
Claims (7)
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CN201810193062.7A CN109100995B (zh) | 2018-03-09 | 2018-03-09 | 基于决策者偏好信息的铝电解节能减排优化方法 |
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CN201810193062.7A CN109100995B (zh) | 2018-03-09 | 2018-03-09 | 基于决策者偏好信息的铝电解节能减排优化方法 |
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CN109100995A CN109100995A (zh) | 2018-12-28 |
CN109100995B true CN109100995B (zh) | 2020-09-29 |
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Families Citing this family (1)
Publication number | Priority date | Publication date | Assignee | Title |
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CN110129832B (zh) * | 2019-06-21 | 2021-04-09 | 广西大学 | 一种铝电解过程槽电压的多目标优化方法 |
Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103699446A (zh) * | 2013-12-31 | 2014-04-02 | 南京信息工程大学 | 基于量子粒子群优化算法的多目标工作流动态调度方法 |
CN105447567A (zh) * | 2015-11-06 | 2016-03-30 | 重庆科技学院 | 基于bp神经网络与mpso算法的铝电解节能减排控制方法 |
CN107045290A (zh) * | 2017-06-14 | 2017-08-15 | 重庆科技学院 | 基于mqpso‑dmpc的反应再生系统优化控制方法 |
Family Cites Families (1)
Publication number | Priority date | Publication date | Assignee | Title |
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US20190359510A1 (en) * | 2018-05-23 | 2019-11-28 | Beijing University Of Technology | Cooperative optimal control method and system for wastewater treatment process |
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2018
- 2018-03-09 CN CN201810193062.7A patent/CN109100995B/zh active Active
Patent Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103699446A (zh) * | 2013-12-31 | 2014-04-02 | 南京信息工程大学 | 基于量子粒子群优化算法的多目标工作流动态调度方法 |
CN105447567A (zh) * | 2015-11-06 | 2016-03-30 | 重庆科技学院 | 基于bp神经网络与mpso算法的铝电解节能减排控制方法 |
CN105447567B (zh) * | 2015-11-06 | 2017-12-05 | 重庆科技学院 | 基于bp神经网络与mpso算法的铝电解节能减排控制方法 |
CN107045290A (zh) * | 2017-06-14 | 2017-08-15 | 重庆科技学院 | 基于mqpso‑dmpc的反应再生系统优化控制方法 |
Non-Patent Citations (5)
Title |
---|
ar-MOEA: A Novel Preference-Based Dominance Relation for Evolutionary Multiobjective Optimization;Jun Yi;《IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION》;20191031;第788-802页 * |
Modified quantum-behaved particle swarm optimization for parameters estimation of generalized nonlinear multi-regressions model based on Choquet integral with outliers;You-Min Jau;《Applied Mathematics and Computation》;20130915;第282-295页 * |
基于决策者偏好区域的多目标粒子群算法研究;麦雄发 等;《计算机应用研究》;20100415;第1301-1304页 * |
基于拥挤距离排序的铝电解多目标优化;易军 等;《仪器仪表学报》;20151115;第2502-2509页 * |
面向反应再生过程的量子粒子群多目标优化;白竣仁 等;《化工学报》;20181206;第750-756页 * |
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Application publication date: 20181228 Assignee: Foshan shangxiaoyun Technology Co.,Ltd. Assignor: Chongqing University of Science & Technology Contract record no.: X2024980003005 Denomination of invention: Optimization method for energy conservation and emission reduction in aluminum electrolysis based on decision-maker preference information Granted publication date: 20200929 License type: Common License Record date: 20240322 Application publication date: 20181228 Assignee: FOSHAN YAOYE TECHNOLOGY Co.,Ltd. Assignor: Chongqing University of Science & Technology Contract record no.: X2024980003003 Denomination of invention: Optimization method for energy conservation and emission reduction in aluminum electrolysis based on decision-maker preference information Granted publication date: 20200929 License type: Common License Record date: 20240322 Application publication date: 20181228 Assignee: Foshan helixing Technology Co.,Ltd. Assignor: Chongqing University of Science & Technology Contract record no.: X2024980003002 Denomination of invention: Optimization method for energy conservation and emission reduction in aluminum electrolysis based on decision-maker preference information Granted publication date: 20200929 License type: Common License Record date: 20240322 |
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