CN108445756B - 基于ar支配关系的铝电解节能减排智能控制方法 - Google Patents
基于ar支配关系的铝电解节能减排智能控制方法 Download PDFInfo
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- CN108445756B CN108445756B CN201810192955.XA CN201810192955A CN108445756B CN 108445756 B CN108445756 B CN 108445756B CN 201810192955 A CN201810192955 A CN 201810192955A CN 108445756 B CN108445756 B CN 108445756B
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- 229910052782 aluminium Inorganic materials 0.000 title claims abstract description 105
- XAGFODPZIPBFFR-UHFFFAOYSA-N aluminium Chemical compound [Al] XAGFODPZIPBFFR-UHFFFAOYSA-N 0.000 title claims abstract description 95
- 238000005868 electrolysis reaction Methods 0.000 title claims abstract description 57
- 238000000034 method Methods 0.000 title claims abstract description 35
- 238000004519 manufacturing process Methods 0.000 claims abstract description 53
- 239000002245 particle Substances 0.000 claims abstract description 51
- 238000005265 energy consumption Methods 0.000 claims abstract description 24
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 22
- 238000013528 artificial neural network Methods 0.000 claims abstract description 16
- 230000000306 recurrent effect Effects 0.000 claims abstract description 14
- 150000001875 compounds Chemical class 0.000 claims abstract description 7
- 230000006870 function Effects 0.000 claims description 51
- 210000004027 cell Anatomy 0.000 claims description 46
- 210000002569 neuron Anatomy 0.000 claims description 41
- 238000012549 training Methods 0.000 claims description 20
- -1 perfluoro compound Chemical class 0.000 claims description 17
- 238000012546 transfer Methods 0.000 claims description 14
- AZDRQVAHHNSJOQ-UHFFFAOYSA-N alumane Chemical compound [AlH3] AZDRQVAHHNSJOQ-UHFFFAOYSA-N 0.000 claims description 10
- 230000009467 reduction Effects 0.000 claims description 9
- 238000004134 energy conservation Methods 0.000 claims description 6
- 238000004364 calculation method Methods 0.000 claims description 3
- 239000003792 electrolyte Substances 0.000 claims description 3
- 230000007246 mechanism Effects 0.000 claims description 3
- 230000008569 process Effects 0.000 abstract description 12
- 239000005431 greenhouse gas Substances 0.000 abstract description 3
- 230000035772 mutation Effects 0.000 abstract description 3
- 238000005457 optimization Methods 0.000 description 8
- 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
- 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
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
- G05B13/042—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance
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- 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
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- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Water Treatment By Electricity Or Magnetism (AREA)
- Electrolytic Production Of Metals (AREA)
- Electrolytic Production Of Non-Metals, Compounds, Apparatuses Therefor (AREA)
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 |
y<sub>1</sub> | y<sub>2</sub> | y<sub>3</sub> | y<sub>4</sub> | x<sub>1</sub> | x<sub>2</sub> | x<sub>3</sub> | x<sub>4</sub> | x<sub>5</sub> | x<sub>6</sub> | x<sub>7</sub> |
99.14 | 3635 | 3.65 | 10835.15 | 1649 | 628 | 2.54 | 1210 | 16.5 | 14.5 | 942 |
98.13 | 3682 | 3.59 | 11527.21 | 1652 | 626 | 2.38 | 1200 | 17.5 | 15 | 925 |
95.37 | 3602 | 3.68 | 10478.32 | 1674 | 617 | 2.47 | 1095 | 17.5 | 15.5 | 935 |
Claims (6)
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Families Citing this family (4)
Publication number | Priority date | Publication date | Assignee | Title |
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CN110232481B (zh) * | 2019-06-17 | 2023-02-14 | 重庆仲澜科技有限公司 | 基于mqpso的天然气管网多目标优化调度方法 |
CN112501655A (zh) * | 2020-11-17 | 2021-03-16 | 湖南力得尔智能科技股份有限公司 | 一种铝电解生产数字化智能管控平台 |
CN113780672B (zh) * | 2021-09-17 | 2023-09-05 | 北京恒泰能联科技发展有限公司 | 基于大数据人工智能的电解槽参数优化方法和系统 |
CN117691880B (zh) * | 2024-02-03 | 2024-05-10 | 西门子能源电气设备(常州)有限公司 | 一种高效率低谐波的电解整流设备及控制方法 |
Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPH10314833A (ja) * | 1997-05-14 | 1998-12-02 | Nippon Light Metal Co Ltd | 直接押出成形用プレスにおけるコンテナシール力制御方法 |
CN105282746A (zh) * | 2015-09-11 | 2016-01-27 | 华东交通大学 | 基于嵌入式粒子群博弈的认知无线网络频谱分配方法 |
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 |
CN107067149A (zh) * | 2017-01-24 | 2017-08-18 | 国网福建省电力有限公司 | 一种评估调峰约束下电网购电组合收益及风险的方法 |
-
2018
- 2018-03-09 CN CN201810192955.XA patent/CN108445756B/zh active Active
Patent Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPH10314833A (ja) * | 1997-05-14 | 1998-12-02 | Nippon Light Metal Co Ltd | 直接押出成形用プレスにおけるコンテナシール力制御方法 |
CN105282746A (zh) * | 2015-09-11 | 2016-01-27 | 华东交通大学 | 基于嵌入式粒子群博弈的认知无线网络频谱分配方法 |
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 |
CN107067149A (zh) * | 2017-01-24 | 2017-08-18 | 国网福建省电力有限公司 | 一种评估调峰约束下电网购电组合收益及风险的方法 |
Non-Patent Citations (5)
Title |
---|
A new quantum-behaved particle swarm optimization based on cultural evolution mechanism for multiobjective problems;Tianyu Liu 等;《Knowledge-Based Systems》;20160316;全文 * |
ar-MOEA A Novel Preference-Based Dominance Relation for Evolutionary Multiobjective Optimization;Jun Yi 等;《IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION》;20191005;全文 * |
Operating Parameters Optimization for the Aluminum Electrolysis Process Using an Improved Quantum-Behaved Particle Swarm Algorithm;Jun Yi 等;《IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS》;20180808;全文 * |
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》;20151130;全文 * |
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;全文 * |
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