化工学报 ›› 2008, Vol. 59 ›› Issue (7): 1768-1772.
• 过程系统工程 • 上一篇 下一篇
严爱军;王普;曾宇
出版日期:
发布日期:
YAN Aijun;WANG Pu;ZENG Yu
Online:
Published:
摘要:
赤铁矿竖炉燃烧过程机理复杂,运行工况变化频繁,使得故障易发,从而导致生产不稳定。将案例推理和软测量技术相结合,提出一种竖炉燃烧过程的智能故障预报方法。软测量模型对难以在线测量的关键工艺参数进行实时测量,基于案例检索与重用的故障预报模型根据过程数据及关键工艺参数软测量值的变化对燃烧过程的典型故障进行趋势预报,采用概率的形式表达诊断结果,并提供操作指导,可以有效避免故障的发生。将建立的故障预报系统应用于竖炉燃烧过程的生产实际中,故障发生率明显降低,表明了方法的有效性。
关键词: 燃烧过程, 故障预报, 案例推理, 软测量
燃烧过程,
Abstract:
Due to its synthetic and complex characteristics,the combustion process in the hematite ore-filled shaft furnace is noted for complex mechanism and frequent change of operating conditions,which results in frequent occurrence of faults and unsteady production. In order to reduce the faults ratio during the combustion process,an intelligent faults prediction approach was developed based on the combination of case-based reasoning(CBR)with soft-sensing. The soft-sensing model could estimate the key technical parameters which were difficult to measure online,and provide some information about the faults. Then,the fault prediction model based on case retrieval and reuse was adopted to make a thorough analysis on the combustion process. The model could provide the occurring probability of some typical faults,followed by corresponding operation instructions. The proposed fault prediction system was applied to the practical combustion process in a shaft furnace,and evidently eliminated the fault ratio.
Key words: 燃烧过程, 故障预报, 案例推理, 软测量
严爱军, 王普, 曾宇. 竖炉燃烧过程智能故障预报系统 [J]. 化工学报, 2008, 59(7): 1768-1772.
YAN Aijun, WANG Pu, ZENG Yu. Intelligent fault prediction system of combustion process in shaft furnace[J]. CIESC Journal, 2008, 59(7): 1768-1772.
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