Operational Parameters and Back Propagation Neural Network (BPNN) Simulation Model of Integration Membrane Bioreactor (IMBR) Treating Sewage from Ship

Abstract:

Nowadays, in order to meet the new standard of IMO for sewage discharged from ship treatment, membrane bioreactor (MBR) was widely used in this field. In this study, a novel bioreactor named integration membrane bioreactor (IMBR) was used to treat sewage from ship. A lab scale experiment was conducted to find the best controlling strategy of operation. The results were as follows: The IMBR had strong adaptability and effluent stability under wide change in VLR which was from 1.2kg/m³.d to 4.3kg/m³.d; The HRT of the IMBR was suggested to be controlled around 6h; The IMBR operator was better in alkali-resistant and weaker in acid-proof, which implied the pH of suitable living environment for aerobic microbe should be higher than 6.5. At the same time, a simulation model of operational parameters was established based on theory of back propagation neural network (BPNN). The simulation model realizes prediction of which were the key impact factor and optimum operational parameters of the IMBR system. Each parameter influencing the performance of the reactor was compared using the method of partitioning connection weights (PCW). The weight of the influence factors was pH value> DO>influent COD in the experimental range.

• Periodical: Advanced Materials Research (Volumes 356-360)
• Pages: 1042-1045
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.356-360.1042
• Online since: October 2011
• Authors: Yue Shi, Liang Guo, Jun Zhou, Run Bai, Xin Li, Peng Liu, Xiang Xiang Wang
• Keywords: BP Neural Network (BPNN), Influence Factor, Integration Membrane Bioreactor (IMBR), Sewage from Ship

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