A novel performance assessment method of the carbon efficiency for iron ore sintering process

过程(计算) 模糊逻辑 计算机科学 航程(航空) 碳纤维 先决条件 工艺工程 数据挖掘 可靠性工程 算法 人工智能 工程类 复合数 操作系统 航空航天工程 程序设计语言
作者
Kailong Zhou,Xin Chen,Min Wu,Yosuke Nakanishi,Weihua Cao,Jie Hu
出处
期刊:Journal of Process Control [Elsevier BV]
卷期号:106: 44-53 被引量:4
标识
DOI:10.1016/j.jprocont.2021.08.011
摘要

Improving carbon efficiency is an effective way to save energy and reduce harmful emission for a sintering process. Optimizing carbon efficiency is an effective way to achieve that goal, and its precondition is to assess the performance of the carbon efficiency. However, there is seldom research about how to assess the carbon efficiency whether it needs to be optimized. To address this, this paper introduces a performance assessment method for evaluating the performance of the carbon efficiency. First, the sintering process and the key characteristics are analyzed, and the carbon efficiency indexes are defined. Second, the structure of the assessment method is presented. The method consists of a prediction model based on three NNs, and an assessment method based on the fuzzy synthetic evaluation method. Two-level combination strategy is proposed to improve prediction performance and assessment accuracy, with the using of bootstrap aggregating, linear combination, and majority voting. Finally, verification based on process data shows that the proposed method can assess the performance of the carbon efficiency with high accuracy. More specially, the prediction errors of the combination model for the CCR are basically in the range of [-2.738 kg/t, 3.442 kg/t], and for the CO/CO2 they are basically in the range of [-8.16 × 10−3, 4.828 × 10−3]. The combination models have better prediction performance than single NNs. Moreover, the assessment accuracy of the proposed method is 87%, which has higher accuracy than other models. This model lays the groundwork of improving the carbon efficiency for sintering process.
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