REQUIMTE/CQFB, Chemistry Department, Faculdade de Ciências e Tecnologia - Universidade Nova de Lisboa, 2829-516 Caparica, Portugal.
J Biotechnol. 2013 Apr 10;164(3):386-95. doi: 10.1016/j.jbiotec.2012.06.026. Epub 2012 Jul 11.
In the present study, the performance of a membrane bioreactor (MBR) was modelled using a hybrid approach based on the activated sludge model number 3 (ASM3) combined with projection to latent structures (PLS) to predict the residuals of the ASM. The application of ASM to MBRs requires frequent re-calibration to adjust the model to variations in influent characteristics, determined through time-consuming analysis and batch tests. Considering this problem, the objective of this study was to improve ASM prediction ability with minimal additional monitoring effort. Hybrid models were developed to predict three MBR performance parameters: mixed liquor suspended solids (MLSS), COD in the permeate (CODp) and nitrite and nitrate concentration in the permeate (NOxp). For PLS modelling of ASM residuals three input strategies were used: (1) analytic and operating data; (2) operating data plus 2D fluorescence spectroscopy; (3) all the data. The first input strategy improved ASM prediction of the three selected outputs, and highlighted the lack of detailed and real-time information from wastewater and operating parameters in the ASM used in this study. In the second input strategy, the incorporation of updated data from 2D fluorescence spectroscopy resulted on better model fitting than in the first input strategy, for all the output parameters studied. Through the hybrid modelling approach it was possible to significantly improve the ASM predictions in real-time using 2D fluorescence measurements and other relevant parameters acquired on-line, without requiring further laboratory analysis. Furthermore, the third input strategy, incorporating all the collected data, did not significantly improve the prediction of the outputs beyond the second strategy. This shows that 2D fluorescence spectroscopy is a comprehensive monitoring tool, able to capture on-line the required information to complement, through hybrid modelling, the mechanistic information described by an ASM.
在本研究中，采用基于活性污泥模型号 3（ASM3）与投影至潜在结构（PLS）相结合的混合方法对膜生物反应器（MBR）的性能进行建模，以预测 ASM 的剩余物。将 ASM 应用于 MBR 需要频繁重新校准，以通过耗时的分析和批量测试来调整模型以适应进水特性的变化。考虑到这个问题，本研究的目的是在最小化额外监测工作量的情况下提高 ASM 的预测能力。开发了混合模型来预测 MBR 的三个性能参数：混合液悬浮固体（MLSS）、透过液中的 COD（CODp）和透过液中的亚硝酸盐和硝酸盐浓度（NOxp）。为了对 ASM 残差进行 PLS 建模，使用了三种输入策略：（1）分析和操作数据；（2）操作数据加二维荧光光谱；（3）所有数据。第一种输入策略提高了 ASM 对三个选定输出的预测能力，并突出了本研究中使用的 ASM 中缺乏详细和实时的废水和操作参数信息。在第二种输入策略中，将二维荧光光谱的更新数据纳入后，与第一种输入策略相比，所有研究的输出参数的模型拟合都得到了改善。通过混合建模方法，使用二维荧光测量和在线获取的其他相关参数，可以实时显著提高 ASM 的预测能力，而无需进一步的实验室分析。此外，第三种输入策略，即纳入所有收集的数据，并没有在第二种策略的基础上显著提高输出的预测能力。这表明二维荧光光谱是一种全面的监测工具，能够在线捕获所需信息，通过混合建模来补充 ASM 描述的机制信息。
