A Dynamic Latent Structure With Time-Varying Parameters for Virtual Sensing of Industrial Process With Irregular Missing Data

A Dynamic Latent Structure With Time-Varying Parameters for Virtual Sensing of Industrial Process With Irregular Missing Data

This paper proposes a novel dynamic latent structure with time-varying parameters for virtual sensing of industrial process with irregular missing data. The proposed latent structure is based on the linear dynamic system (LDS) model. In order to capture the time-varying process characteristics, a Ka...

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Bibliographic Details
Main Authors: Ze Ying, Yun Wang, Jun Wang, Yuchen He
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Data-driven process monitoring
virtual sensors
irregularly missing data
linear dynamic systems (LDS)
linear time-varying parameters
Kalman filtering
Online Access:https://ieeexplore.ieee.org/document/9437231/

Internet

https://ieeexplore.ieee.org/document/9437231/

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