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HE Zhimin; DONG Chunhua; QI Wei
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何志敏; 董春华; 齐崴
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Abstract: In the enzymatic membrane reactor for separating casein hydrolysate, backflushing technology has been used to decrease the fouling of the membrane. Predication of the backflushing efficiency poses a complex non-linear problem as the system integrates enzymatic hydrolysis, membrane separation and periodic backflushing together. In this paper an alternative artificial neural network approach is developed to predict the backflushing efficiency as a function of duration and interval. A contour plot of backflushing performance is presented to model these effects, and the backflushing conditions have been optimized as duration of 10 s and interval of 10 min using this neural network. Also, simple neural networks are established to predict the time evolution of flux before and after backflushing. The results predicted by the models are in good agreement with the experimental data, and the average deviations for all the cases are well within ±5%. The neural network approach is found to be capable of modeling the backflushing with confidence.
Key words: backflushing, neural network, model, optimize, predict, casein
摘要: In the enzymatic membrane reactor for separating casein hydrolysate, backflushing technology has been used to decrease the fouling of the membrane. Predication of the backflushing efficiency poses a complex non-linear problem as the system integrates enzymatic hydrolysis, membrane separation and periodic backflushing together. In this paper an alternative artificial neural network approach is developed to predict the backflushing efficiency as a function of duration and interval. A contour plot of backflushing performance is presented to model these effects, and the backflushing conditions have been optimized as duration of 10 s and interval of 10 min using this neural network. Also, simple neural networks are established to predict the time evolution of flux before and after backflushing. The results predicted by the models are in good agreement with the experimental data, and the average deviations for all the cases are well within ±5%. The neural network approach is found to be capable of modeling the backflushing with confidence.
关键词: 酶膜耦合反应器;反冲过程;神经网络模型;最优化;酪蛋白
HE Zhimin, DONG Chunhua, QI Wei. The Neural Network Model for Backflushing in Enzymatic Membrane Reactor[J]. .
何志敏,董春华,齐崴. 酶膜耦合反应器中反冲过程的神经网络模拟[J]. CIESC Journal.
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https://hgxb.cip.com.cn/EN/Y2005/V13/I6/809