| 用于燃煤锅炉热效率在线计算的虚拟煤质数据库的建立 |
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| 引用本文： | 陈雪,杨东伟,顾晨恺,管坚,郁鸿凌.用于燃煤锅炉热效率在线计算的虚拟煤质数据库的建立[J].上海理工大学学报,2019,41(6):546-551. |
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| 作者姓名： | 陈雪 杨东伟 顾晨恺 管坚 郁鸿凌 |
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| 作者单位： | 上海理工大学 能源与动力工程学院, 上海 200093,上海理工大学 能源与动力工程学院, 上海 200093,上海理工大学 能源与动力工程学院, 上海 200093,中国特种设备检测研究院, 北京 100029,上海理工大学 能源与动力工程学院, 上海 200093 |
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| 基金项目： | 国家重点研发计划（2017YFF0209806） |
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| 摘 要： | 燃煤锅炉热效率在线计算模型的实用性及可操作性高度依赖于燃用燃料的成分和类型,为了减少煤质的复杂性及多样性、现场燃煤煤质成分分析误差以及人为离线输入参数的不准确性对锅炉热效率在线计算的影响,拟构建可供在线计算燃煤热效率调用的虚拟煤质数据库。通过对工业锅炉常用煤种成分、来源及种类进行线性回归并运用统计分析以及聚类分析等数学算法,搭建虚拟煤质数据库。为了验证煤质数据库的适用性,借助神经网络算法对燃煤的计算发热量和化验发热量进行了对比分析,结果显示,误差在工业用煤的测量误差范围内。所建的燃煤数据库能有效地实现锅炉变工况运行时的热效率在线测算。
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| 关 键 词： | 煤质数据库 燃煤发热量 工业锅炉 热效率 聚类算法 神经网络 |
| 收稿时间： | 2018/7/30 0:00:00 |
Establishment of Virtual Coal Database for Online Calculation of Thermal Efficiency of Coal-Fired Boilers |
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| CHEN Xue,YANG Dongwei,GU Chenkai,GUAN Jian and YU Hongling.Establishment of Virtual Coal Database for Online Calculation of Thermal Efficiency of Coal-Fired Boilers[J].Journal of University of Shanghai For Science and Technology,2019,41(6):546-551. |
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| Authors: | CHEN Xue YANG Dongwei GU Chenkai GUAN Jian and YU Hongling |
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| Institution: | School of Energy and Power Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China,School of Energy and Power Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China,School of Energy and Power Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China,China Special Equipment Inspection and Research Institute, Beijing 100029, China and School of Energy and Power Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China |
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| Abstract: | The practicability and operability of online calculating model of boiler efficiency is highly dependent on the composition and type of fuel. In order to reduce the complexity and diversity of coal quality, the analysis error of on-site coal quality and the influence of the inaccuracy of artificial offline input parameters on the boiler thermal efficiency online calculating, a virtual coal quality database which can be used for online calculation of thermal efficiency of coal-fired boiler was proposed. Through the linear regression of the compositions, sources, and types of coal commonly used in industrial boilers and the use of mathematical algorithms such as statistical analysis and cluster analysis, a virtual coal quality database was constructed. In order to verify the applicability of the coal quality database, the calculated calorific value of the coal was compared and analyzed with the help of the neural network algorithm. The results show that the error is within the measurement error range of the industrial coal. The built coal-fired database can effectively realize the online calculation of the thermal efficiency of the boiler when is operating under variable conditions. |
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| Keywords: | coal quality database calorific value of coal industrial boiler thermal efficiency cluster computing methods neural network |
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