Wastewater treatment is a complicated dynamic process affected by microbial, chemical and physical factors. Faults are inevitable during the operation of modified sequencing batch reactors(MSBRs) because of the uncert...Wastewater treatment is a complicated dynamic process affected by microbial, chemical and physical factors. Faults are inevitable during the operation of modified sequencing batch reactors(MSBRs) because of the uncertainty of various factors. Abnormal MSBR results require fault diagnosis to determine the cause of failure and implement appropriate measures to adjust system operations. Bayesian network(BN) is a powerful knowledge representation tool that deals explicitly with uncertainty. A BN-based approach to diagnosing wastewater treatment systems based on MSBR is developed in this study. The network is constructed using the knowledge derived from literature and elicited from experts, and it is parametrized using independent data from a pilot test.A one-year pilot study is conducted to verify the diagnostic analysis. The proposed model is reasonable, and the diagnosis results are accurate. This approach can be applied with minimal modifications to other types of wastewater treatment plants.展开更多
In this study,the effect of number of stages and bioreactor type on the removal performance of a sequential anaerobic-aerobic process employing activated sludge for the treatment of a simulated textile dyeing wastewat...In this study,the effect of number of stages and bioreactor type on the removal performance of a sequential anaerobic-aerobic process employing activated sludge for the treatment of a simulated textile dyeing wastewater containing three commercial reactive azo dyes was considered.Two stage processes performed better than one stage ones,both in terms of overall organic and color removal,as well as the higher contribution of anaerobic stage to the overall removal performance,thereby making them a more energy efficient option.The employment of a moving bed sequencing batch biofilm reactor,which uses both suspended and attached biomass,for the implementation of the anaerobic stage of the process,was compared with a sequencing batch reactor that only employs suspended biomass.The results showed that,although there was no meaningful difference in biomass concentration between the two bioreactors,the latter reactor had better performance in terms of chemical oxygen demand(COD)removal efficiency and rate and color removal rate.Further exploratory tests revealed a difference between the roles of suspended and attached bacterial populations,with the former yielding better color removal whilst the latter had better COD removal performance.The sequential anaerobic–aerobic process,employing an aerobic membrane bioreactor in the aerobic stage resulted in COD and color removal of 77.1±7.9%and 79.9±1.5%,respectively.The incomplete COD and color removal was attributed to the presence of soluble microbial products in the effluent and the autoxidation of dye reduction metabolites,respectively.Also,aerobic partial mineralization of the dye reduction metabolites,was experimentally observed.展开更多
基金the Foundation of State Key Laboratory of Ocean Engineering of Shanghai Jiao Tong University(No.GKZD010071)
文摘Wastewater treatment is a complicated dynamic process affected by microbial, chemical and physical factors. Faults are inevitable during the operation of modified sequencing batch reactors(MSBRs) because of the uncertainty of various factors. Abnormal MSBR results require fault diagnosis to determine the cause of failure and implement appropriate measures to adjust system operations. Bayesian network(BN) is a powerful knowledge representation tool that deals explicitly with uncertainty. A BN-based approach to diagnosing wastewater treatment systems based on MSBR is developed in this study. The network is constructed using the knowledge derived from literature and elicited from experts, and it is parametrized using independent data from a pilot test.A one-year pilot study is conducted to verify the diagnostic analysis. The proposed model is reasonable, and the diagnosis results are accurate. This approach can be applied with minimal modifications to other types of wastewater treatment plants.
基金supported by Takmiliran textile dyeing factory(272219601)Materials and Energy Research Center(MERC)(99392003).
文摘In this study,the effect of number of stages and bioreactor type on the removal performance of a sequential anaerobic-aerobic process employing activated sludge for the treatment of a simulated textile dyeing wastewater containing three commercial reactive azo dyes was considered.Two stage processes performed better than one stage ones,both in terms of overall organic and color removal,as well as the higher contribution of anaerobic stage to the overall removal performance,thereby making them a more energy efficient option.The employment of a moving bed sequencing batch biofilm reactor,which uses both suspended and attached biomass,for the implementation of the anaerobic stage of the process,was compared with a sequencing batch reactor that only employs suspended biomass.The results showed that,although there was no meaningful difference in biomass concentration between the two bioreactors,the latter reactor had better performance in terms of chemical oxygen demand(COD)removal efficiency and rate and color removal rate.Further exploratory tests revealed a difference between the roles of suspended and attached bacterial populations,with the former yielding better color removal whilst the latter had better COD removal performance.The sequential anaerobic–aerobic process,employing an aerobic membrane bioreactor in the aerobic stage resulted in COD and color removal of 77.1±7.9%and 79.9±1.5%,respectively.The incomplete COD and color removal was attributed to the presence of soluble microbial products in the effluent and the autoxidation of dye reduction metabolites,respectively.Also,aerobic partial mineralization of the dye reduction metabolites,was experimentally observed.
