基于煤岩组分和镜质组反射率的焦炭质量预测模型
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摘要
为准确预测焦炭质量,采用MSS2000全自动智能型煤焦显微分析系统,测定炼焦煤样的煤岩组分、活惰比和镜质组平均最大反射率,分析煤样所制备焦炭的质量。采用SPSS软件建立基于煤岩参数的焦炭质量预测模型。模型验证结果表明,焦炭的抗碎强度、耐磨强度、化学反应性、反应后强度与煤岩组分和镜质组平均最大反射率的复相关系数均大于0.879,P值小于0.01。预测模型可信度较高,为焦化厂优化配煤、提高焦炭质量提供了参考。
This paper seeks to obtain an accurate prediction of coke quality. The research involves measuring coal components,ratio of reactive and inert components,and average maximum vitrinite reflectance( R—max) of coking coal using MSS2000 Automatic Intelligent Coal Particle Microanalysis System; analyzing coke qualities of as-prepared coking coal samples; and thereby using SPSS software to build a coke quality prediction model based on coke parameters. The verified results demonstrate that the prediction model owes its higher reliability to the multi-correlation coefficient greater than 0. 879 between the coke crushing strength,abrasion strength,chemical reactivity,and coke strength after reaction and coal components and average maximum vitrinite reflectance,and to P value less than 0. 01. This model may provides a reference for optimizing coal blending and improving coke quality.
This paper seeks to obtain an accurate prediction of coke quality. The research involves measuring coal components,ratio of reactive and inert components,and average maximum vitrinite reflectance( R—max) of coking coal using MSS2000 Automatic Intelligent Coal Particle Microanalysis System; analyzing coke qualities of as-prepared coking coal samples; and thereby using SPSS software to build a coke quality prediction model based on coke parameters. The verified results demonstrate that the prediction model owes its higher reliability to the multi-correlation coefficient greater than 0. 879 between the coke crushing strength,abrasion strength,chemical reactivity,and coke strength after reaction and coal components and average maximum vitrinite reflectance,and to P value less than 0. 01. This model may provides a reference for optimizing coal blending and improving coke quality.
引文
[1]毕学工.焦炭质量与高炉冶炼关系的再思考[J].过程工程学报,2009,9(S1):438-442.
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[4]王海燕.煤岩学与炼焦配煤技术的发展[J].煤质技术,2004(6):39-41.
[5]Diaz F E,Barriocanal C,Diez M A,et al.Applying TAG parameters in coke quality prediction models[J].Journal of Analytical and Applied Pyrolysis,2007,79(1):154-160.
[6]Butcher L A F,Crelling J C.History of applied coal petrology in the United States:early history of the application of coal petrography in the steel industry[J].International Journal of Coal Geology,2000,42(2/3):93-101.
[7]周师庸,周淑仪.烟煤容纳惰性物质能力[J].炼焦化学,1984(6):4-8.
[8]燕瑞华,高志军,耿印权,等.镜质组反射率分布图在配煤炼焦中的应用[J].燃料与化工,2001,32(5):227-230.
[9]白云起,白洋,孔小红,等.配合煤的镜质组反射率分布与焦炭强度预测[J].黑龙江科技大学学报,2014,24(2):123-126.
[10]杨扬,杨逸.10kg试验焦炉在预测焦炭质量中的应用[J].科技情报开发与经济,2009,19(11):202-203
[2]白青子,王天威,刘亚林.炼焦原料煤镜质组的反射率及分布[J].黑龙江科技大学学报,2014,24(2):119-122.
[3]田英奇.配煤炼焦试验优化与神经网络焦炭质量预测模型的研究[D].上海:华东理工大学,2016.
[4]王海燕.煤岩学与炼焦配煤技术的发展[J].煤质技术,2004(6):39-41.
[5]Diaz F E,Barriocanal C,Diez M A,et al.Applying TAG parameters in coke quality prediction models[J].Journal of Analytical and Applied Pyrolysis,2007,79(1):154-160.
[6]Butcher L A F,Crelling J C.History of applied coal petrology in the United States:early history of the application of coal petrography in the steel industry[J].International Journal of Coal Geology,2000,42(2/3):93-101.
[7]周师庸,周淑仪.烟煤容纳惰性物质能力[J].炼焦化学,1984(6):4-8.
[8]燕瑞华,高志军,耿印权,等.镜质组反射率分布图在配煤炼焦中的应用[J].燃料与化工,2001,32(5):227-230.
[9]白云起,白洋,孔小红,等.配合煤的镜质组反射率分布与焦炭强度预测[J].黑龙江科技大学学报,2014,24(2):123-126.
[10]杨扬,杨逸.10kg试验焦炉在预测焦炭质量中的应用[J].科技情报开发与经济,2009,19(11):202-203