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Operational parameters and back propagation neural network (BPNN) simulation model of integration membrane bioreactor (IMBR) treating sewage from ship

机译:从船舶处理污水的整体膜生物反应器(IMBR)的操作参数和后传播神经网络(BPNN)仿真模型

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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/m~3·d to 4.3kg/m~3·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.
机译:如今,为了满足从船舶处理排出的污水的新标准,膜生物反应器(MBR)被广泛用于该领域。在该研究中,使用了一个名为Intoction膜生物反应器(IMBR)的新型生物反应器来处理船舶的污水。进行了实验室规模实验以找到最佳的操作控制策略。结果如下:IMBR在VLR的宽变化下具有较强的适应性和污水稳定性,其为1.2kg / m〜3·d至4.3kg / m〜3·d;建议将IMBR的HRT控制在6小时内; IMBR算子在耐碱性和耐酸体中较弱,含有适当的有氧微生物的合适生活环境的pH值应高于6.5。同时,基于背传播神经网络(BPNN)理论建立了操作参数的仿真模型。仿真模型实现了预测,其是IMBR系统的关键影响因子和最佳操作参数。使用分配连接权重(PCW)的方法进行比较影响电抗器性能的每个参数。影响因子的重量是实验范围内的pH值> DO>影响COD。

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