Improved Mahalanobis Distance Based JITL-LSTM Soft Sensor for Multiphase Batch Processes

نویسندگان

چکیده

To predict key variables of complicated batch processes, the long short-term memory (LSTM) soft sensor is developed to deal with both data nonlinearity and dynamics. extract proper historical samples implement real-time modeling scheme model updating strategy, just-in-time learning (JITL) algorithm widely used at selection stage LSTM sensor. However, multiphase issue processes are not considered for conventional JITL-LSTM In this paper, a Mahalanobis distance based JITL framework integrate phase recognition strategy into similarity measurement scheme, by which an extra step identification can be avoided accuracy significantly improved. Thus, from different operating phases recognized without additional step. By use Distance Soft Sensor, probability mismatch reduced so that quality prediction promoted. Two simulation cases provided verify effectiveness proposed method consisting fed-batch reactor process penicillin fermentation process.

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ژورنال

عنوان ژورنال: IEEE Access

سال: 2021

ISSN: ['2169-3536']

DOI: https://doi.org/10.1109/access.2021.3079184