Data-driven monitoring and diagnosing of abnormal furnace conditions in blast furnace ironmaking: An integrated PCA-ICA method
Principal component analysis (PCA) and independent component analysis (ICA) have been
widely used for process monitoring in process industry. Since the operation data of blast …
widely used for process monitoring in process industry. Since the operation data of blast …
A multiobjective evolutionary nonlinear ensemble learning with evolutionary feature selection for silicon prediction in blast furnace
In the blast furnace ironmaking process, accurate prediction of silicon content in molten iron
is of great significance for maintaining stable furnace conditions, improving hot metal quality …
is of great significance for maintaining stable furnace conditions, improving hot metal quality …
Kalman filter-based data-driven robust model-free adaptive predictive control of a complicated industrial process
The automatic control of blast furnace (BF) ironmaking process has always been an
important yet arduous task in metallurgic engineering and automation. In this article, a novel …
important yet arduous task in metallurgic engineering and automation. In this article, a novel …
[PDF][PDF] 基于Bootstrap 和ICS-MKELM 算法的大坝变形预测
王晓玲， 谢怀宇， 王佳俊， 陈文龙， 蔡志坚， 刘宗显 - 水力发电学报, 2020 - slfdxb.cn
传统大坝预测方法难以适应坝体变形序列的高维非线性特征, 且仅能以点值的形式预测大坝变形
, 未能有效量化由数据随机噪声, 输入样本的主观确定, 参数的随机选择等引起的结果不确定性 …
, 未能有效量化由数据随机噪声, 输入样本的主观确定, 参数的随机选择等引起的结果不确定性 …
Temperature measurement and compensation method of blast furnace molten iron based on infrared computer vision
The temperature of molten iron at the taphole of blast furnace (BF) is an important parameter
that reflects molten iron quality and BF conditions. It is not easy to measure the temperature …
that reflects molten iron quality and BF conditions. It is not easy to measure the temperature …
Abnormality monitoring in the blast furnace ironmaking process based on stacked dynamic target-driven denoising autoencoders
Accurate monitoring of abnormalities is of great significance to the stable operation of the
blast furnace ironmaking process. This article proposes a data-driven model to accurately …
blast furnace ironmaking process. This article proposes a data-driven model to accurately …
[PDF][PDF] 基于数据的流程工业生产过程指标预测方法综述
陈龙， 刘全利， 王霖青， 赵珺， 王伟 - 自动化学报, 2017 - aas.net.cn
摘要生产过程关键指标的预测对于流程工业生产调度, 安全生产和节能环保有着重要作用. 目前,
已有多种基于工业生产数据提出的生产过程指标预测方法, 主要涉及特征(变量) 选择 …
已有多种基于工业生产数据提出的生产过程指标预测方法, 主要涉及特征(变量) 选择 …
A novel deep interval prediction model with adaptive interval construction strategy and automatic hyperparameter tuning for wind speed forecasting
Y Xie, C Li, G Tang, F Liu - Energy, 2021 - Elsevier
Wind energy is a renewable energy source with great development potential. However, its
inherent instability and randomness have brought great challenges to the maximum …
inherent instability and randomness have brought great challenges to the maximum …
Prediction of multiple molten iron quality indices in the blast furnace ironmaking process based on attention-wise deep transfer network
Molten iron quality (MIQ) indices prediction based on data-driven models is an important
way to monitor product quality and smelting status in the blast furnace ironmaking process …
way to monitor product quality and smelting status in the blast furnace ironmaking process …
基于LSTM-RNN 模型的铁水硅含量预测
李泽龙， 杨春节， 刘文辉， 周恒， 李宇轩 - 化工学报, 2018 - hgxb.cip.com.cn
针对高炉炼铁是一个动态过程, 具有大延迟, 工况复杂的特性. 采用LSTM-RNN
模型进行硅含量预测, 充分发挥了其处理时间序列时挖掘前后关联信息的优势 …
模型进行硅含量预测, 充分发挥了其处理时间序列时挖掘前后关联信息的优势 …