洁净煤技术

2021, v.27;No.132(02) 220-224

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应用不同机器学习算法预测化学链中氧载体性能
Applying different machine learning algorithms to predict the performance of oxygen carriers in chemical-looping

阎永亮;查健锐;段伦博;CLOUGH Peter;
YAN Yongliang;ZHA Jianrui;DUAN Lunbo;CLOUGH Peter;School of Water,Energy and Environment,Cranfield University;Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education,Southeast University;

摘要(Abstract):

低成本和高性能的氧载体材料筛选是化学链技术未来商业应用的关键。超过1 000种材料被作为氧载体在化学链条件下进行测试。其中,矿石和工业副产品作为氧载体最近引起关注,其成本低、供应方便,特别是与固体燃料具有充分的反应性。然而,这些材料具有高度可变的成分,影响其在化学链中的性能,采用试验方法逐个测试成本巨大。运用新兴的机器学习算法,以天然锰矿为对象,将已有的试验数据作为训练集,预测含锰矿物在化学链反应中的性能,并对比支持向量机和人工神经网络2种算法在预测过程中的表现。结果显示,这2种算法对训练集内的数据均有较好准确性,但对新输入值预测的准确性、鲁棒性方面存在差异。支持向量机可以避免神经网络在小样本训练集下存在的过度拟合现象。灵敏度分析表明氧载体锰含量变化对反应特性的影响较大,而比表面积的影响较小。
Developing high-performance and low-cost oxygen carrying materials is the key to the future commercial application of chemical-looping processes. Over 1 000 materials have been tested as the oxygen carriers for chemical-looping processes. Among them,ores and industrial by-products as oxygen carriers have recently attracted much attention recently due to their low cost and availability,especially the sufficient reactivity with the solid fuels. However,these materials have highly variable compositions,which strongly influences the performance in chemical-looping. It costs a lot to test one by one. Taking natural manganese ore as the object,and taking the existing experimental data as the training set,the new machine learning algorithm was used to predict the performance of manganese bearing minerals in chemical chain reaction,and compare the performance of support vector machine and artificial neural network in the prediction process.The results show that the two algorithms have good accuracy for the data in the training set,but there are differences in the accuracy and robustness of the new input value prediction. Support vector machine can avoid the over fitting phenomenon of neural network in small sample training set. The sensitivity analysis shows that the change of manganese content in oxygen carrier has a great influence on the reaction characteristics,while the effect of specific surface area is small.

关键词(KeyWords): 化学链燃烧;氧载体;机器学习;人工神经网络;支持向量机
chemical-looping combustion;oxygen carriers;machine learning;artificial neural network;support vector machine

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作者(Author): 阎永亮;查健锐;段伦博;CLOUGH Peter;
YAN Yongliang;ZHA Jianrui;DUAN Lunbo;CLOUGH Peter;School of Water,Energy and Environment,Cranfield University;Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education,Southeast University;

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DOI: 10.13226/j.issn.1006-6772.CCUS20093003

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