| 燃煤锅炉低氮氧化物燃烧特性的神经网络预报 |
| 摘要点击 2384 全文点击 3448 投稿时间：2001-04-20 修订日期：2001-06-09 |
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| 中文关键词 锅炉 NOx 飞灰含碳量 人工神经网络 |
| 英文关键词 utility boiler NOx emission unburned carbon content artificial neural network |
| DOI 10.13227/j.hjkx.20020204 |
| 作者 | 单位 | | 周昊 | 浙江大学热能工程研究所能源清洁利用和环境工程教育部重点实验室,杭州,310027 | | 茅建波 | 浙江大学热能工程研究所能源清洁利用和环境工程教育部重点实验室,杭州,310027 | | 池作和 | 浙江大学热能工程研究所能源清洁利用和环境工程教育部重点实验室,杭州,310027 | | 蒋啸 | 浙江大学热能工程研究所能源清洁利用和环境工程教育部重点实验室,杭州,310027 | | 王正华 | 浙江大学热能工程研究所能源清洁利用和环境工程教育部重点实验室,杭州,310027 | | 岑可法 | 浙江大学热能工程研究所能源清洁利用和环境工程教育部重点实验室,杭州,310027 |
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| 中文摘要 |
| 大型燃煤电站锅炉的低NOx燃烧技术日益受到关注,但NOx的排放特性复杂,受煤种、锅炉设计结构和操作参数等多种因素影响.在对某台600MW四角切圆燃煤电站锅炉的NOx排放特性和飞灰含碳量特性进行多工况热态测试的基础上,应用人工神经网络的非线性动力学特性及自学习特性,建立了大型四角切圆燃烧锅炉NOx排放特性和燃烧经济性的神经网络模型,并对此模型进行了校验.结果表明,该模型能根据燃煤特性及各种操作参数准确预报锅炉在不同工况下的NOx排放和飞灰含碳量特性,可为大型电站锅炉通过燃烧调整降低NOx排放和提高锅炉燃烧效率提供有效手段. |
| 英文摘要 |
| More attention was paid to the low NOx combustion property of the high capacity tangential firing boiler, but the NOx emission and unburned carbon content in fly ash of coal burned boiler were complicated, they were affected by many factors, such as coal character, boiler's load, air distribution, boiler style, burner style, furnace temperature, excess air ratio, pulverized coal fineness and the uniformity of the air and coal distribution, etc. In this paper, the NOx emission property and unburned carbon content in fly ash of a 600MW utility tangentially firing coal burned boiler was experimentally investigated, and taking advantage of the nonlinear dynamics characteristics and self learning characteristics of artificial neural network, an artificial neural network model on low NOx combustion property of the high capacity boiler was developed and verified. The results illustrated that such a model can predicate the NOx emission concentration and unburned carbon content under various operating conditions, if combined with the optimization algorithm, the operator can find the best operation condition of the low NOx combustion. |
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