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Nonlinear dynamic industrial process fault detection based on attention-enhanced LSTM autoencoder

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Transactions of the Institute of Measurement and Control

Published online on

Abstract

Transactions of the Institute of Measurement and Control, Ahead of Print.
In the field of complex industrial process monitoring, capturing multivariate relationships in data is a major challenge for traditional shallow models. To address this, this paper proposes an attention-enhanced long short-term memory autoencoder (AELSTM-...