| 基于改进主观贝叶斯方法识别电熔镁炉异常工况 |
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| 引用本文： | 袁杰,王姝,王福利,孙晓辉. 基于改进主观贝叶斯方法识别电熔镁炉异常工况[J]. 东北大学学报(自然科学版), 2021, 42(2): 153-159. DOI: 10.12068/j.issn.1005-3026.2021.02.001 |
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| 作者姓名： | 袁杰 王姝 王福利 孙晓辉 |
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| 作者单位： | (1.东北大学 信息科学与工程学院， 辽宁 沈阳110819； 2.东北大学 流程工业综合自动化国家重点实验室， 辽宁 沈阳110819； 3.大连天籁安全风险管理技术有限公司， 辽宁 大连 116600) |
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| 基金项目： | 国家自然科学基金资助项目;矿冶过程自动化国家重点实验室开放基金资助项目 |
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| 摘 要： | 电熔镁炉熔炼过程信息包含大量的不确定性,基于大数据分析的方法难以应用.为准确识别电熔镁炉熔炼过程的异常工况,提出一种基于改进的主观贝叶斯在线规则推理方法.传统的主观贝叶斯方法参数赋值范围过大,针对这一问题,使用映射函数将参数赋值范围缩小到有限区间,以提高方法的实用性.在规则推理时,使用模糊隶属度函数对观察和证据进行模糊...
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| 关 键 词： | 电熔镁炉 异常工况识别 主观贝叶斯 不确定推理 模糊函数 |
Abnormal Condition Recognition Based on Improved Subjective Bayesian Method for Fused Magnesium Furnace |
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| YUAN Jie,WANG Shu,WANG Fu-li,SUN Xiao-hui. Abnormal Condition Recognition Based on Improved Subjective Bayesian Method for Fused Magnesium Furnace[J]. Journal of Northeastern University(Natural Science), 2021, 42(2): 153-159. DOI: 10.12068/j.issn.1005-3026.2021.02.001 |
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| Authors: | YUAN Jie WANG Shu WANG Fu-li SUN Xiao-hui |
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| Affiliation: | 1. School of Information Science & Engineering， Northeastern University， Shenyang 110819， China; 2. State Key Laboratory of Synthetical Automation for Process Industries， Northeastern University， Shenyang 110819， China; 3. Tianlai Security Risk Management Technology Co.， Ltd.， Dalian 116600， China. |
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| Abstract: | It is difficult for big data analysis to be applied to the smelting process of fused magnesium furnace because of a lot of uncertain information of the process. In order to identify abnormal conditions accurately， an online rule reasoning method based on improved subjective Bayesian is proposed. In view of the problem that the parameter value range of the traditional subjective Bayesian method is too wide， the mapping function is used to limit the value range to a finite interval， which improves the practicability of the method. In order to improve the robustness and accuracy of condition recognition， the fuzzy membership function is utilized to match the observation and evidence in the reasoning. Simulation results show that the method can effectively describe the uncertain information in the rules and accurately identify the abnormal conditions in the smelting process of fused magnesium furnace. |
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| Keywords: | fused magnesium furnace abnormal condition recognition subjective Bayesian uncertain reasoning fuzzy function, |
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