|
|
Progress in research on mathematical model of energy consumption of iron ore sintering process |
WANG Hai-dong1,YU Hai-zhao1,FAN Xiao-hui1,LI Hai-liang1,JING Tao1,2,GUO Hui1 |
(1. School of Minerals Processing and Bioengineering, Central South University, Changsha 410083, Hunan, China 2. Zhongye Changtian International Engineering Co., Ltd., Changsha 410205, Hunan, China) |
|
|
Abstract Research developments of mathematical models of the energy consumption of iron ore sintering process were summarized. The energy consumption analysis and the energy management, including the evaluation model of energy efficiency such as the heat balance model, the solid consumption prediction model, the carbon efficiency model, the exergy analysis model in sintering process, and the optimization of sintering process parameters were introduced. At the same time, the future research direction in the area was predicted: innovate methods of the evaluation of energy efficiency, finding the energy weak link in the sintering process, building the mathematical model to evaluate the energy consumption of the sintering process scientifically, optimizing the process parameters under the constraints of certain parameters and state parameters. The ultimate goal is to increase the energy efficiency of the sintering process and achieve green production.
|
Received: 20 March 2018
Published: 26 October 2018
|
|
|
|
[1] |
范晓慧.铁矿造块数学模型与专家系统[M]. 北京: 科学出版社, 2013.
|
[1] |
范晓慧.铁矿造块数学模型与专家系统[M]. 北京: 科学出版社, 2013.
|
[2] |
GB 21256 -2013, 粗钢烧结主要工序单位产品能源消耗限额[S].
|
[2] |
GB 21256 -2013, 粗钢烧结主要工序单位产品能源消耗限额[S].
|
[3] |
胡长庆, 张玉柱, 张春霞.烧结过程物质流和能量流分析[J].烧结球团, 2007, 32(1):16-21
|
[3] |
胡长庆, 张玉柱, 张春霞.烧结过程物质流和能量流分析[J].烧结球团, 2007, 32(1):16-21
|
[4] |
胡 兵, 王兆才, 李宗平, 等.烧结工序能耗精细化管理及其软件开发[J].中国冶金, 2016, 26(9):12-17
|
[4] |
胡 兵, 王兆才, 李宗平, 等.烧结工序能耗精细化管理及其软件开发[J].中国冶金, 2016, 26(9):12-17
|
[5] |
付明辉.钢铁烧结生产工艺过程能源管理系统的研究[D]. 长沙: 中南大学, 2010.
|
[5] |
付明辉.钢铁烧结生产工艺过程能源管理系统的研究[D]. 长沙: 中南大学, 2010.
|
[6] |
胡志远, 楼国锋, 温 治, 等.烧结热过程质量和能量平衡的诊断及分析[J].冶金自动化, 2008, 32(5):20-24
|
[6] |
胡志远, 楼国锋, 温 治, 等.烧结热过程质量和能量平衡的诊断及分析[J].冶金自动化, 2008, 32(5):20-24
|
[7] |
周茂军, 何志军, 袁 兵, 等.宝钢号烧结机质能平衡测试与分析[J].烧结球团, 2011, 36(6):9-13
|
[7] |
周茂军, 何志军, 袁 兵, 等.宝钢号烧结机质能平衡测试与分析[J].烧结球团, 2011, 36(6):9-13
|
[8] |
李宗平, 胡兵, 曾 辉.基于烧结热平衡理论的固体燃耗精确计算技术研究与实现[A]. 2014年度全国烧结球团技术交流年会论文集[C]. 厦门: 烧结球团编辑部, 2014: 28~31.
|
[8] |
李宗平, 胡兵, 曾 辉.基于烧结热平衡理论的固体燃耗精确计算技术研究与实现[A]. 2014年度全国烧结球团技术交流年会论文集[C]. 厦门: 烧结球团编辑部, 2014: 28~31.
|
[9] |
韩庆虹, 金永龙, 张军红.人工神经网络在烧结固体燃耗预测中的应用[J].冶金能源, 2005, 24(2):9-11
|
[9] |
韩庆虹, 金永龙, 张军红.人工神经网络在烧结固体燃耗预测中的应用[J].冶金能源, 2005, 24(2):9-11
|
[10] |
孟 辉, 乔 非, 李 莉.基于BP 神经网络的烧结能耗预测模型[J].机械工程师, 2012, (2):45-47
|
[10] |
孟 辉, 乔 非, 李 莉.基于BP 神经网络的烧结能耗预测模型[J].机械工程师, 2012, (2):45-47
|
[11] |
王俊凯, 乔 非, 祝 军, 等.基于支持向量机的烧结能耗及性能指标预测模型[J].同济大学学报自然科学版, 2014, 42(8):1256-1260
|
[11] |
王俊凯, 乔 非, 祝 军, 等.基于支持向量机的烧结能耗及性能指标预测模型[J].同济大学学报自然科学版, 2014, 42(8):1256-1260
|
[12] |
CHEN Xiao-xia, SHE Jin-hua, CHEN Xin, et al.Modeling method of carbon efficiency in iron ore sintering process[A]. 2016 IEEE international conference on industrial technology (ICIT)[C]. Taibei: IEEE, 2016: 1033~1038.
|
[12] |
CHEN Xiao-xia, SHE Jin-hua, CHEN Xin, et al.Modeling method of carbon efficiency in iron ore sintering process[A]. 2016 IEEE international conference on industrial technology (ICIT)[C]. Taibei: IEEE, 2016: 1033~1038.
|
[13] |
陈 鑫, 翁卫卫, 吴 敏, 等.混沌粒子群算法的烧结碳耗神经网络模型[J].计算机与应用化学, 2013, 30(10):1223-1226
|
[13] |
陈 鑫, 翁卫卫, 吴 敏, 等.混沌粒子群算法的烧结碳耗神经网络模型[J].计算机与应用化学, 2013, 30(10):1223-1226
|
[14] |
翁卫卫, 陈鑫, 吴敏, 等.基于遗传小波神经网络的烧结过程碳耗模型[A]. 第32届中国控制会议论文集(CCC2013)[C], 西安: 中国自动化学会控制理论专业委员会, 2013: 1860~1865.
|
[14] |
翁卫卫, 陈鑫, 吴敏, 等.基于遗传小波神经网络的烧结过程碳耗模型[A]. 第32届中国控制会议论文集(CCC2013)[C], 西安: 中国自动化学会控制理论专业委员会, 2013: 1860~1865.
|
[15] |
CHEN Xiao-xia, SHE Jin-hua, CHEN Xin, et al.Discrete wavelet transfer based BPNN for calculating carbon efficiency of sintering process[J].Journal of advanced computational intelligence and intelligent informatics, 2016, 20(7):1070-1076
|
[15] |
CHEN Xiao-xia, SHE Jin-hua, CHEN Xin, et al.Discrete wavelet transfer based BPNN for calculating carbon efficiency of sintering process[J].Journal of advanced computational intelligence and intelligent informatics, 2016, 20(7):1070-1076
|
[16] |
CHEN Xiao-xia, CHEN Xin, SHE Jin-hua, et al.A hybrid time series prediction model based on recurrent neural network and double joint linear–nonlinear extreme learning network for prediction of carbon efficiency in iron ore sintering process[J].Neurocomputing, 2017, 249(C):128-139
|
[16] |
CHEN Xiao-xia, CHEN Xin, SHE Jin-hua, et al.A hybrid time series prediction model based on recurrent neural network and double joint linear–nonlinear extreme learning network for prediction of carbon efficiency in iron ore sintering process[J].Neurocomputing, 2017, 249(C):128-139
|
[17] |
CHEN Xiao-xia, CHEN Xin, SHE Jin-hua, et al.A hybrid just-in-time soft sensor for carbon efficiency of iron ore sintering process based on feature extraction of cross-sectional frames at discharge end[J].Journal of process control, 2017, (54):14-24
|
[17] |
CHEN Xiao-xia, CHEN Xin, SHE Jin-hua, et al.A hybrid just-in-time soft sensor for carbon efficiency of iron ore sintering process based on feature extraction of cross-sectional frames at discharge end[J].Journal of process control, 2017, (54):14-24
|
[18] |
翁卫卫.基于成品率预测的烧结过程综合焦比计算模型[D]. 长沙: 中南大学, 2014.
|
[18] |
翁卫卫.基于成品率预测的烧结过程综合焦比计算模型[D]. 长沙: 中南大学, 2014.
|
[19] |
CHEN Xiao-xia, CHEN Xin, SHE Jin-hua, et al.Hybrid multistep modeling for calculation of carbon efficiency of iron ore sintering process based on yield prediction[J].Neural Computing & Applications, 2016, 28(6):1193-1207
|
[19] |
CHEN Xiao-xia, CHEN Xin, SHE Jin-hua, et al.Hybrid multistep modeling for calculation of carbon efficiency of iron ore sintering process based on yield prediction[J].Neural Computing & Applications, 2016, 28(6):1193-1207
|
[20] |
向 德.面向碳效优化的烧结过程CO/CO2计算建模研究[D]. 长沙: 中南大学, 2013.
|
[20] |
向 德.面向碳效优化的烧结过程CO/CO2计算建模研究[D]. 长沙: 中南大学, 2013.
|
[21] |
XU Ben, CHEN Xin, WU Min, et al.A cascade prediction model of COCO2 in the sintering process[J].Journal of Advanced Computational Intelligence and Intelligent Informatics, 2017, 21(5):785-794
|
[21] |
XU Ben, CHEN Xin, WU Min, et al.A cascade prediction model of COCO2 in the sintering process[J].Journal of Advanced Computational Intelligence and Intelligent Informatics, 2017, 21(5):785-794
|
[22] |
吴复忠, 李军旗, 金会心, 等.烧结工序的物质流和能量?流分析[J].贵州科学, 2011, 29(2):76-79
|
[22] |
吴复忠, 李军旗, 金会心, 等.烧结工序的物质流和能量?流分析[J].贵州科学, 2011, 29(2):76-79
|
[23] |
胡兵, 贺新华, 王兆才, 等.烧结工序?流分析及评价[J].中国冶金, 2015, 25(9):47-51
|
[23] |
胡兵, 贺新华, 王兆才, 等.烧结工序?流分析及评价[J].中国冶金, 2015, 25(9):47-51
|
[24] |
王芳.烧结?耗和烧结焦比计算建模方法研究[D]. 长沙: 中南大学, 2013.
|
[24] |
王芳.烧结?耗和烧结焦比计算建模方法研究[D]. 长沙: 中南大学, 2013.
|
[25] |
罗国民, 文五四, 刘志强, 等.韶钢烧结工序用能模型开发与能流优化分析[J].烧结球团, 2011, 36(3):14-17
|
[25] |
罗国民, 文五四, 刘志强, 等.韶钢烧结工序用能模型开发与能流优化分析[J].烧结球团, 2011, 36(3):14-17
|
[26] |
范晓慧, 王海东.烧结过程数学模型与人工智能[M]. 长沙: 中南大学出版社, 2002.
|
[26] |
范晓慧, 王海东.烧结过程数学模型与人工智能[M]. 长沙: 中南大学出版社, 2002.
|
[27] |
马俊杰, 吴 敏, 李 勇.烧结配料过程焦粉最低配比计算方法[J].化工学报, 2012, 63(9):2688-2696
|
[27] |
马俊杰, 吴 敏, 李 勇.烧结配料过程焦粉最低配比计算方法[J].化工学报, 2012, 63(9):2688-2696
|
[28] |
HUANG Xiao-xian, FAN Xiao-hui, CHEN Xu-ling, et al.Bed permeability state prediction model of sintering process based on data mining technology[J].ISIJ International, 2016, 56(12):2113-2117
|
[28] |
HUANG Xiao-xian, FAN Xiao-hui, CHEN Xu-ling, et al.Bed permeability state prediction model of sintering process based on data mining technology[J].ISIJ International, 2016, 56(12):2113-2117
|
[29] |
FAN Xiao-hui, HUANG Xiao-xian, CHEN Xu-ling, et al.Research and development of the intelligent control of iron ore sintering process based on fan frequency conversion[J].Ironmaking & Steelmaking, 2016, 43(7):488-493
|
[29] |
FAN Xiao-hui, HUANG Xiao-xian, CHEN Xu-ling, et al.Research and development of the intelligent control of iron ore sintering process based on fan frequency conversion[J].Ironmaking & Steelmaking, 2016, 43(7):488-493
|
[30] |
冯朝辉, 张 华, 王艳红.烧结工序能耗预测与优化研究[J].烧结球团, 2012, 37(6):13-17
|
[30] |
冯朝辉, 张 华, 王艳红.烧结工序能耗预测与优化研究[J].烧结球团, 2012, 37(6):13-17
|
[31] |
LI Zong-ping, FAN Xiao-hui, CHEN Guo, et al.Optimization of iron ore sintering process based on ELM model and multi-criteria evaluation[J].Neural Computing & Applications, 2017, 28(8):2247-2253
|
[31] |
LI Zong-ping, FAN Xiao-hui, CHEN Guo, et al.Optimization of iron ore sintering process based on ELM model and multi-criteria evaluation[J].Neural Computing & Applications, 2017, 28(8):2247-2253
|
[32] |
CHEN Xin, CHEN Xiao-xia, Wu Min, et al.Modeling and optimization method featuring multiple operating modes for improving carbon efficiency of iron ore sintering process[J].Control Engineering Practice, 2016, (54):117-128
|
[32] |
CHEN Xin, CHEN Xiao-xia, Wu Min, et al.Modeling and optimization method featuring multiple operating modes for improving carbon efficiency of iron ore sintering process[J].Control Engineering Practice, 2016, (54):117-128
|
[33] |
DU Sheng, WU Min, CHEN Xin, et al.Design of an optimization and control system for carbon efficiency in the green manufacturing of sinter ore[A]. 2017 36th Chinese Control Conference (CCC) [C], Dalian: Technical Committee on Control Theory, Chinese Association of Automation, 2017: 4470~4475.
|
[33] |
DU Sheng, WU Min, CHEN Xin, et al.Design of an optimization and control system for carbon efficiency in the green manufacturing of sinter ore[A]. 2017 36th Chinese Control Conference (CCC) [C], Dalian: Technical Committee on Control Theory, Chinese Association of Automation, 2017: 4470~4475.
|
[1] |
JI Xiu-mei1,2,WANG Long1,GAO Ke-wei2,LIU Jie1. Application of ELM to predict plate rolling force[J]. JOURNAL OF IRON AND STEEL RESEARCH , 2020, 32(5): 393-399. |
[2] |
CAO Yun-fei, YU Wei, LIU Min, JIANG Rui, WANG Chun. Austenite grain growth model of 38MnSiVS bearing microalloyed forging steel[J]. Iron and Steel, 2020, 55(5): 103-108. |
[3] |
. Analysis and control of slag inclusion defect of low carbon steel slab[J]. , 2020, 45(2): 0-0. |
[4] |
. Study on air excess coefficient setting and precision control of CSP heating furnace[J]. , 2019, 44(4): 0-0. |
[5] |
KANG Yong-lin, TIAN Peng, ZHU Guo-ming. Progress and trend on hot wide strip endless rolling technology[J]. Iron and Steel, 2019, 54(3): 1-8. |
[6] |
SHI Xian- zhe,,DU Shi- wen,,CHEN Shuang- mei,. Processing properties analysis of medium carbon steel based on hot processing map[J]. , 2019, 31(1): 31-39. |
|
|
|
|