Data-driven soft sensors in blast furnace ironmaking: a survey
The blast furnace is a highly energy-intensive, highly polluting, and extremely complex
reactor in the ironmaking process. Soft sensors are a key technology for predicting molten …
reactor in the ironmaking process. Soft sensors are a key technology for predicting molten …
Graph convolutional network soft sensor for process quality prediction
The nonlinear time-varying characteristics of the process industry can be modeled using
numerous data-driven soft sensor methods. However, the intrinsic relationships among the …
numerous data-driven soft sensor methods. However, the intrinsic relationships among the …
Semi-supervised LSTM with historical feature fusion attention for temporal sequence dynamic modeling in industrial processes
In modern industrial processes, the data-driven soft sensor technology has been widely
used for the prediction of key quality variables. Due to the important of dynamics and …
used for the prediction of key quality variables. Due to the important of dynamics and …
Deep learning with nonlocal and local structure preserving stacked autoencoder for soft sensor in industrial processes
Deep learning-based soft sensor has been widely used for quality prediction in modern
industry. Traditional deep learning like stacked autoencoder (SAE) only captures the feature …
industry. Traditional deep learning like stacked autoencoder (SAE) only captures the feature …
A novel conformable fractional nonlinear grey multivariable prediction model with marine predator algorithm for time series prediction
H Zhu, L Chong, W Wu, W Xie - Computers & Industrial Engineering, 2023 - Elsevier
To promote the development of multivariate prediction modelling in small sample
environments, this paper constructs a new multivariate prediction model named CFDNGBM …
environments, this paper constructs a new multivariate prediction model named CFDNGBM …
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 …
A review of just‐in‐time learning‐based soft sensor in industrial process
W Sheng, J Qian, Z Song… - The Canadian Journal of …, 2024 - Wiley Online Library
Data‐driven soft sensing approaches have been a hot research field for decades and are
increasingly used in industrial processes due to their advantages of easy implementation …
increasingly used in industrial processes due to their advantages of easy implementation …
Dynamic data reconciliation for enhancing the performance of kernel learning soft sensor models considering measurement noise
In modern industrial processes, data-driven soft sensor models avoiding the limitations of
measurement techniques and expensive costs are developed for process monitoring and …
measurement techniques and expensive costs are developed for process monitoring and …
Transductive transfer broad learning for cross-domain information exploration and multigrade soft sensor application
Without sufficient labeled data, the construction of accurate soft-sensor models for
multigrade chemical processes is challenging. To alleviate the dilemma, a transductive …
multigrade chemical processes is challenging. To alleviate the dilemma, a transductive …
[HTML][HTML] Improved operation of a large-scale blast furnace using a hybrid dynamic model based optimizing control scheme
P Azadi, H Elwan, R Klock, S Engell - Journal of Process Control, 2023 - Elsevier
In the steel industry, the blast furnace (BF) is a core piece of equipment along the route from
iron ore to steel, with the largest energy consumption and CO 2 emissions. The stable …
iron ore to steel, with the largest energy consumption and CO 2 emissions. The stable …