Confidence rule base for soot blowing demand based on production data mining

QIAN Hong; SONG Liang; CHEN Qiqi; CHEN Gang

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Confidence rule base for soot blowing demand based on production data mining

Thermal Power Generation Issue 5, (2017)

更新时间：2025-09-28

- Confidence rule base for soot blowing demand based on production data mining
- 作者机构：
  
  1. 上海电力学院自动化工程学院,上海,200090
  2. 华能上海石洞口第一电厂,上海,200942
- 作者简介：
- 基金信息：
- DOI：
  CLC： TK16
- Published Online：27 May 2017，
  
  Published：2017
- 稿件说明：
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QIAN Hong, SONG Liang, CHEN Qiqi, et al. Confidence rule base for soot blowing demand based on production data mining[J]. Thermal Power Generation, 2017, (5).
DOI：

QIAN Hong, SONG Liang, CHEN Qiqi, et al. Confidence rule base for soot blowing demand based on production data mining[J]. Thermal Power Generation, 2017, (5). DOI：

摘要

为对锅炉积灰结渣受热面吹灰优化，以锅炉燃烧特性和吸热特性为理论依据对生产数据进行挖掘处理，建立吹灰需求度置信规则库。运用数理统计、贝叶斯理论，结合现场运行专家经验，完成吹灰策略集和征兆集的提取、规则的表示和规则变量的设定，并对规则库进行测试。结果表明，本吹灰需求度置信规则库对领域专家吹灰经验的知识描述符合电厂实际吹灰需求，达到了吹灰优化的目的。

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