Adaptive Temporal–Spatial Pyramid Variational Autoencoder Model for Multirate Dynamic Chemical Process Soft Sensing Application
Bingbing Shen,
Zeyu Yang,
Le Yao
Abstract:Data-driven soft sensors play an important role in practical processes and have been widely applied. They provide realtime prediction of quality variables and then guide production and improve product quality. In practical chemical production processes, nonlinear dynamic multirate data is widespread and challenging to model. This paper innovatively proposes a temporal−spatial pyramid variational autoencoder (TS-PVAE) model for the nonlinear temporal−spatial feature pyramid extraction from multirate data. This … Show more
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