ZHANG W, ZHANG C H.Soft measurement based on DAK-FNN for effluent ammonia nitrogen[J].Journal of Henan Polytechnic University(Natural Science) ,2023,42(2):134-143.

doi:10.16186/j.cnki.1673-9787.2021070052

Received:2021/07/14

Revised:2021/11/16

Published:2023/03/25

Soft measurement based on DAK-FNN for effluent ammonia nitrogen

ZHANG Wei, ZHANG Chunhui

School of Electrical Engineering and Automation，Henan Polytechnic University，Jiaozuo 454000，Henan，China

Abstract:The performance of the established model with incomplete real-time data is poor.To solve this problem，a soft measurement method based on data-knowledge-driven fuzzy neural network （DAK-FNN） was proposed for effluent ammonia nitrogen under the framework of transfer learning，which not only could use data of the current scene，but could make full use of knowledge of the source scene.First，in order to effectively combine knowledge of the source scene with data of the current scene，a knowledge transfer method was proposed based on the idea of transfer learning.It could obtain knowledge contained from a large amount of historical data in the reference model，and could transfer knowledge to the target model.The parameters of the target model were fine-tuned through online learning method to improve the model accuracy.Second，in order to improve the generalization performance of the model，a structure adjustment method was proposed based on long and short-term memory mechanism，which could divide the neurons of target model into core neurons and non-core neurons.The structure could be adjusted by setting different neuron addition and deletion thresholds.Effluent ammonia nitrogen prediction experiment were carried out，the results showed that the proposed method had higher online prediction accuracy and better real-time performance compared with other methods.

Key words:fuzzy neural network;data driven;knowledge driven;fine-tuning;effluent ammonia nitrogen;soft measurement

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