Adaptive non-linear soft sensor for quality monitoring in refineries using Just-in-Time Learning—Generalized regression neural network approach
HK Mohanta, AK Pani - Applied Soft Computing, 2022 - Elsevier
Real time estimation of target quality variables using soft sensor relevant to time varying
process conditions will be a significant step forward in effective implementation of Industry …
process conditions will be a significant step forward in effective implementation of Industry …
Quality variable prediction for nonlinear dynamic industrial processes based on temporal convolutional networks
Soft sensors have been extensively developed to estimate the difficult-to-measure quality
variables for real-time process monitoring and control. Process nonlinearities and dynamics …
variables for real-time process monitoring and control. Process nonlinearities and dynamics …
Semi-supervised ensemble support vector regression based soft sensor for key quality variable estimation of nonlinear industrial processes with limited labeled data
Soft sensor technique has become a promising solution to enable real-time estimations of
difficult-to-measure quality variables in industrial processes. However, traditional soft sensor …
difficult-to-measure quality variables in industrial processes. However, traditional soft sensor …
Novel just-in-time learning-based soft sensor utilizing non-Gaussian information
This brief develops a novel just-in-time (JIT) learning-based soft sensor for modeling of
industrial processes. The recorded data is assumed to exhibit non-Gaussian signal …
industrial processes. The recorded data is assumed to exhibit non-Gaussian signal …
Efficient JITL framework for nonlinear industrial chemical engineering soft sensing based on adaptive multi-branch variable scale integrated convolutional neural …
Y Chen, A Li, X Li, D Xue, J Long - Advanced Engineering Informatics, 2023 - Elsevier
Just-in-time Learning (JITL) is a soft measurement method commonly used in industrial
processes, which can update local models in real-time to solve the problem of inaccurate …
processes, which can update local models in real-time to solve the problem of inaccurate …
[HTML][HTML] Support vector regression modeling in recursive just-in-time learning framework for adaptive soft sensing of naphtha boiling point in crude distillation unit
HK Mohanta, AK Pani - Petroleum Science, 2021 - Elsevier
Prediction of primary quality variables in real time with adaptation capability for varying
process conditions is a critical task in process industries. This article focuses on the …
process conditions is a critical task in process industries. This article focuses on the …
A soft sensor model based on CNN-BiLSTM and IHHO algorithm for Tennessee Eastman process
Y Li, T Peng, W Sun, C Ji, Y Wang, Z Tao, C Zhang… - Measurement, 2023 - Elsevier
Accurate measurement of key variables plays an important role in on-line monitoring and
control optimization of industrial processes. Soft sensor provides an effective method for …
control optimization of industrial processes. Soft sensor provides an effective method for …
Mixed kernel principal component weighted regression based on just-in-time learning for soft sensor modeling
Soft sensors have been extensively applied for predicting difficult-to-measure quality
variables. However, industrial processes are often characterized with the nonlinearity and …
variables. However, industrial processes are often characterized with the nonlinearity and …
Just-in-time learning based soft sensor with variable selection and weighting optimized by evolutionary optimization for quality prediction of nonlinear processes
Abstract Just-in-time (JIT) learning based soft sensors have been widely used for predicting
product quality variables of nonlinear processes. They dynamically build online local models …
product quality variables of nonlinear processes. They dynamically build online local models …
Data-driven soft sensor development based on deep learning technique
In industrial process control, some product qualities and key variables are always difficult to
measure online due to technical or economic limitations. As an effective solution, data …
measure online due to technical or economic limitations. As an effective solution, data …