王宁会

个人信息Personal Information

研究员

博士生导师

硕士生导师

性别:男

毕业院校:东北师范大学

学位:学士

所在单位:电子信息与电气工程学部

电子邮箱:nhwang@dlut.edu.cn

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Smelting condition identification for a fused magnesium furnace based on an acoustic signal

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论文类型:期刊论文

发表时间:2017-06-01

发表刊物:JOURNAL OF MATERIALS PROCESSING TECHNOLOGY

收录刊物:SCIE、EI

卷号:244

页面范围:231-239

ISSN号:0924-0136

关键字:Acoustic signal; Fused magnesium furnace; Linear predictive coding; Principal component analysis

摘要:To promote energy efficiency during fused.magnesium furnace smelting, four smelting states were introduced in the smelting stage: an unmelted state, semi-molten state, molten state, and overheating state. A smelting identification system to distinguish these smelting states was developed through the use of linear predictive coding and a principal component analysis algorithm. A new smelting condition identification system was obtained. Corresponding pilot productions were conducted to compare the differences between employing the method and not employing the method. All of the pilot production data showed that feeding raw materials over time during the overheating state and decreasing current injection in the molten state could reduce energy consumption as well as increase crystal purity. (C) 2016 Published by Elsevier B.V.