| 基于案例推理的竖炉故障预报系统 |
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| 引用本文： | 严爱军,柴天佑,王普.基于案例推理的竖炉故障预报系统[J].控制与决策,2008,23(2):177-181. |
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| 作者姓名： | 严爱军 柴天佑 王普 |
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| 作者单位： | 1. 北京工业大学,电子信息与控制工程学院,北京,100022
2. 东北大学,自动化研究中心,沈阳,110004 |
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| 基金项目： | 国家重点基础研究发展计划(973计划)，北京工业大学博士科研流动基金 |
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| 摘 要： | 为降低竖望炉焙烧过程的故障发生率,基于故障机理的分析,将过程参量预报与案例推理技术相集成,提出了竖炉焙烧过程的智能故障预报方法.参量量预报模型对不易在线连续测量但能反映故障征兆的关键工艺参数进行实时预报,在此基础上,采用案例推理技术对焙烧过程进行全面分析并给出一些典型故障发生的概率和操作指导.将所建立的故障预报系统成功应用于竖炉焙烧过程的生产实际中,故障发生率明显降低,取得了显著应用成效.
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| 关 键 词： | 故障预报 案例推理 参量预报 竖炉 智能 |
| 文章编号： | 1001-0920（2008）02-0177-05 |
| 收稿时间： | 2006-11-23 |
| 修稿时间： | 2007-01-29 |
Fault prediction system using case-based reasoning for shaft furnace status |
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| YAN Ai-jun,CHAI Tian-you,WANG Pu.Fault prediction system using case-based reasoning for shaft furnace status[J].Control and Decision,2008,23(2):177-181. |
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| Authors: | YAN Ai-jun CHAI Tian-you WANG Pu |
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| Affiliation: | YAN Ai-jun1,CHAI Tian-you2,WANG Pu1(1.College of Electronic Information , Control Engineering,Beijing University of Technology,Beijing 100022,China,2.Research Center of Automation,Northeastern University,Shenyang 110004,China.) |
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| Abstract: | For reducing the fault ratio of shaft ore-roasting furnace,based on the analysis of the fault mechanism and combination of case-based reasoning(CBR) and variables prediction,an intelligent fault prediction approach is proposed for the shaft furnace roasting process.The prediction model of the process variables performs to predict key technical parameters as the fault symptoms that is hard to measure online.The probability of the typical fault and their operation guidance with the help of case-based reasonin... |
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| Keywords: | Fault prediction Case-based reasoning Variable prediction Shaft furnace Intelligent |
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