降维和聚类筛选可燃固废基元及其热重表征

杨潇潇; 甘雨; 周会; 李清海; 张衍国

doi:10.13205/j.hjgc.202210016

降维和聚类筛选可燃固废基元及其热重表征

doi: 10.13205/j.hjgc.202210016

1. 清华大学能源与动力工程系热科学与动力工程教育部重点实验室二氧化碳资源利用与减排技术北京市重点实验室, 北京 100084;
2. 南京天洑软件有限公司, 南京 211106

基金项目:

国家重点研发计划(2020YFC1910101)

广东省重点领域研发计划(2020B1111380001)

详细信息

作者简介:
杨潇潇(1989-),女,工程师,主要研究方向为固体废弃物资源化利用。yangxiaoxiao2589@126.com

通讯作者:
张衍国(1968-),男,教授,主要研究方向为劣质燃料的燃烧、余热利用、固体燃料的热转化等技术。zhangyg@tsinghua.edu.cn

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出版历程
- 收稿日期: 2021-10-15

THERMOGRAVIMETRIC CHARACTERIZATION OF COMBUSTIBLE SOLID WASTE WITH PSEUDO-COMPONENTS SELECTED BY DIMENSION REDUCTION AND CLUSTERING METHOD

1. Beijing Key Laboratory of CO₂ Utilization and Reduction Technology, Key Laboratory for Thermal Science and Power Engineering of Ministry of Education, Department of Energy and Power Engineering, Tsinghua University, Beijing 100084, China;
2. Nanjing Tianfu Software Co., Ltd, Nanjing 211106, China

摘要

摘要: 可燃固废无害化处理需求日益增长,采用焚烧方法可有效实现其资源化、减量化和无害化。可燃固废的热化学特性对燃烧过程的组织具有重要意义,但由于可燃固废来源和种类的多样性,可燃固废特别是混合可燃固废的热化学性质表征是一个亟待解决的难题。以某几种典型的可燃固废作为基元,可以简化、高效、系统地表征其他可燃固废的热化学特性。采用主成分分析方法进行降维,再通过层次聚类方法将可燃固废归类,基于完备性、独立性和确定性3种基元性质和中心原则、简单原则2种筛选机制的约束下,量化比选出乳胶手套、硬塑料袋、PE、PET、淀粉、木质素、纤维素和半纤维素8种物质作为基元,并对基元的热重特性进行表征,依据热重特性分析并建立了可燃固废热转化基元表征的方法。并通过对一种工业可燃固废(包装布)进行拟合(灰色关联度高达0.989),验证了降维和聚类筛选基元方法的实用性和准确性,为可燃固废的热转化特性和处置方法提供参考。
- 可燃固废 /
- 降维 /
- 聚类 /
- 基元 /
- 热重表征
Abstract: The demand for the harmless treatment of combustible solid waste (CSW) is increasing, and the incineration method can effectively realize the resource utilization, reduction and harmlessness of CSW. The thermochemical properties of CSW are of great significance in the organization of the combustion process. Due to the diversity of sources and types of CSW, the characterization of the thermochemical properties of CSW, especially CSW mixture is an urgent problem. If some typical CSW is used as "pseudo-components", the thermochemical characteristics of other CSW can be simplified, efficiently and systematically characterized. In this study, the principal component analysis (PCA) method was used to reduce the dimension, and then the CSW was classified with the selection of the pseudo-components based on the criteria of completeness, independence and certainty, as well as the central criteria and the simple criteria. Finally, eight species including latex gloves, hard plastic bags, PE, PET, starch, lignin, cellulose and hemicellulose were selected as pseudo-components. And the above several pseudo-components had been characterized by thermogravimetric analysis, based on this, a method for characterizing the heat conversion unit of CSW was established. Fitting industrial CSW, which gray relation grade was as high as 0.989, the practicability and accuracy of the method of dimension reduction and clustering were verified. This study established a method for characterizing the thermal conversion of CSW, which could provide a reference for the thermal conversion and disposal of CSW.
- combustible solid waste /
- dimension reduction /
- clustering /
- pseudo-component /
- thermogravimetric characterization

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参考文献(22)

[1]	国家统计局. 中国统计年鉴[EB/OL]. (2011-09-20)[2021-07-28]. http://www.stats.gov.cn/tjsj/ndsj/2011/indexch.htm. 2011.
[2]	国家统计局. 中国统计年鉴[EB/OL]. (2020-09-23)[2021-07-28]. http://www.stats.gov.cn/tjsj/ndsj/2020/indexch.htm. 2020.
[3]	贾川. 我国生活垃圾焚烧发展现状与趋势[J]. 环境与可持续发展. 2019, 44(4):59-62.
[4]	金宜英, 邴君妍, 罗恩华, 等. 基于分类趋势下的我国生活垃圾处理技术展望[J]. 环境工程, 2019, 37(9):149-153 ,130.
[5]	杨威, 郑仁栋, 张海丹, 等. 中国垃圾焚烧发电工程的发展历程与趋势[J]. 环境工程, 2020, 38(12):124-129.
[6]	马涛, 王晓磊, 洪涛, 等. 我国城市生活垃圾能源化利用潜力时空分析及影响因素分析[J]. 节能技术, 2021, 39(2):99-106.
[7]	席北斗, 刘东明, 李鸣晓, 等. 我国固废资源化的技术及创新发展[J]. 环境保护, 2017, 45(20):16-19.
[8]	DONG Z G, LIU Z H, ZHANG X, et al. Pyrolytic characteristics of hemicellulose, cellulose and lignin under CO₂ atmosphere[J]. Fuel, 2019, 256:115890.
[9]	LIU Q, WANG S R, WANG K G, et al. Pyrolysis of wood species based on the compositional analysis[J]. The Korean Journal of Chemical Engineering, 2009, 26(2):548-553.
[10]	YANG H P, YAN R, CHEN H P, et al. In-depth investigation of biomass pyrolysis based on three major components:hemicellulose, cellulose and lignin[J]. Energy & Fuels:an American Chemical Society journal, 2006, 20(1):388-393.
[11]	LONG Y Q, LI Q H, ZHOU H, et al. A grey-relation-based method (GRM) for thermogravimetric (TG) data analysis[J]. Journal of Material Cycles and Waste Management, 2017, 20(2):1026-1035.
[12]	LONG Y Q, MENG A H, CHEN S, et al. Pyrolysis and combustion of typical wastes in a newly designed macro thermogravimetric analyzer:characteristics and simulation by model components[J]. Energy & Fuels, 2017, 31(7):7582-7590.
[13]	龙艳秋, 李清海, 周会, 等. 可燃固体废弃物热转化特性的基元表征方法[J]. 清华大学学报(自然科学版), 2017, 57(12):1324-1330.
[14]	蒙爱红, 龙艳秋, 周会, 等. 可燃固体废弃物热化学反应表征探索[J]. 清华大学学报(自然科学版), 2014, 54(2):235-239.
[15]	ZHOU H, LONG Y Q, MENG A H, et al. Classification of municipal solid waste components for thermal conversion in waste-to-energy research[J]. Fuel, 2015, 145:151-157.
[16]	ZHOU H, MENG A H, LONG Y Q, et al. Classification and comparison of municipal solid waste based on thermochemical characteristics[J]. Journal of the Air & Waste Management Association, 2014, 64(5):597-616.
[17]	ZHOU H, LONG Y Q, MENG A H, et al. Thermogravimetric characteristics of typical municipal solid waste fractions during co-pyrolysis[J]. Waste Manag, 2015, 38:194-200.
[18]	朱景福, 李雪. 玉米叶片病害彩色图像识别的降维和聚类方法[J]. 江苏农业科学, 2016, 44(7):350-354.
[19]	李远博, 曹菡. 基于PCA降维的协同过滤推荐算法[J]. 计算机技术与发展, 2016, 26(2):26-30.
[20]	殷锋, 曹旭, 漆翔宇. 基于聚类的推荐算法综述[J]. 西南民族大学学报(自然科学版), 2021, 47(3):303-309.
[21]	RAMOUS-GUAJARDO A B. A hierarchical clustering method for random intervals based on a similarity measure[J]. Computational Statistics, 2021,37:229-261.
[22]	龙艳秋. 可燃固体废弃物热转化特性的基元表征方法研究[D]. 北京:清华大学,2017.