Adaptive Soft Sensor Modeling Based on Weighted Supervised Latent Factor Analysis with Selectively Integrated Moving Windows
Sign Up to like & getrecommendations! Published in 2017 at "IFAC-PapersOnLine"
DOI: 10.1016/j.ifacol.2017.08.2334
Abstract: Abstract An adaptive soft sensor modeling method based on weighted supervised latent factor analysis is proposed. In conventional moving window based adaptive soft sensor, predictive model is constructed only with the latest process information. To… read more here.
Keywords: soft sensor; weighted supervised; based weighted; adaptive soft ... See more keywords
Ensemble deep relevant learning framework for semi-supervised soft sensor modeling of industrial processes
Sign Up to like & getrecommendations! Published in 2021 at "Neurocomputing"
DOI: 10.1016/j.neucom.2021.07.086
Abstract: Abstract Deep learning has been growing in popularity for soft sensor modeling of nonlinear industrial processes, infeuality-related variables. However, applications may be highly nonlinear, and the quantity of labeled samples is considerably limited. The extraction… read more here.
Keywords: industrial processes; sensor modeling; ensemble deep; soft sensor ... See more keywords
A Novel Soft Sensor Modeling Approach Based on Difference-LSTM for Complex Industrial Process
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Industrial Informatics"
DOI: 10.1109/tii.2021.3110507
Abstract: The main purpose of soft sensor modeling is to capture the dynamic nonlinear features between the easy-to-measure auxiliary variables and the difficult-to-measure key variables. However, in complex industrial process, it is a challenging work due… read more here.
Keywords: complex industrial; industrial process; process; soft sensor ... See more keywords
A Supervised Bidirectional Long Short-Term Memory Network for Data-Driven Dynamic Soft Sensor Modeling
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Instrumentation and Measurement"
DOI: 10.1109/tim.2022.3152856
Abstract: Data-driven soft sensors have been widely adopted in industrial processes to learn hidden knowledge automatically from process data, then to monitor difficult-to-measure quality variables. However, to extract and utilize useful dynamic latent features accurately for… read more here.
Keywords: sensor modeling; supervised bidirectional; soft sensor; data driven ... See more keywords
Soft Sensor Modeling Method Based on Target-Guided Related Feature Learning and Its Application
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Instrumentation and Measurement"
DOI: 10.1109/tim.2022.3219482
Abstract: Currently, soft sensors have been extensively used in complex industrial processes. How to learn effective features from nonlinear process data is the core task of building precise soft sensors. Deep learning, a type of feature… read more here.
Keywords: feature; sensor modeling; soft sensor; target guided ... See more keywords