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Design of urban sludge emission reduction optimisation strategy based on fuzzy neural network

Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Urban sewage sludge treatment is important for sustainable utilisation and virtuous cycle of freshwater resources. However, with the improvement of sewage discharge standards, ensuring stable operation of sewage sludge treatment plants is becoming an urgent problem to be solved in the sewage treatment industry. This paper proposes a FNN control framework based on different working conditions to optimise the whole process of municipal sewage sludge treatment and discharge. The framework first divides the working conditions according to the weather, forming a separate feature and an input vector together with the typical indicators of other sewage treatment plants. Then the FNN is used to complete the control and optimisation of various indicators, achieving the dual objectives of reducing energy consumption and optimising water quality. Finally, the model is tested for the tracking index of sewage flow. The results demonstrate that the FNN control method used has significantly lower MAE than the single method in the two indexes of energy consumption and water quality evaluation. This provides new ideas for the optimisation of urban sewage sludge treatment process in the future. Overall, the paper effectively highlights the importance of urban sewage sludge treatment and presents a well-designed FNN control framework for optimising the treatment process. Additionally, the paper could benefit from further elaboration on the significance of the results obtained, and suggestions for future research in this area.
Rocznik
Strony
243--250
Opis fizyczny
Bibliogr. 18 poz., rys., tab.
Twórcy
autor
  • Design Institute NO.3, Shanghai Municipal Engineering Design and Research Institute (Group) Co., Ltd., Shanghai 200092, China
autor
  • Design Institute NO.3, Shanghai Municipal Engineering Design and Research Institute (Group) Co., Ltd., Shanghai 200092, China
autor
  • Design Institute NO.3, Shanghai Municipal Engineering Design and Research Institute (Group) Co., Ltd., Shanghai 200092, China
  • Design Institute NO.3, Shanghai Municipal Engineering Design and Research Institute (Group) Co., Ltd., Shanghai 200092, China
autor
  • Design Institute NO.3, Shanghai Municipal Engineering Design and Research Institute (Group) Co., Ltd., Shanghai 200092, China
Bibliografia
  • [1] Wu CH, Tsai SB, Liu W, Shao XF, Xia YK, Wacławek M. Green environment and sustainable development: methods and applications. Ecol Chem Eng S. 2021;28(4):467-70. DOI: 10.2478/eces-2021-0030.
  • [2] Liu W, Tsai SB, Wu CH, Shao X, Wacławek M. Corporate environmental management and sustainable operation: theory and application. Ecol Chem Eng S. 2022;29(3):283-5. DOI: 10.2478/eces-2022-0020.
  • [3] Obotey Ezugbe E, Rathilal S. Membrane technologies in wastewater treatment: a review. Membranes. 2020;10(5):89. DOI: 10.3390/membranes10050089.
  • [4] Crini G, Lichtfouse E. Advantages and disadvantages of techniques used for wastewater treatment. Environ Chem Lett. 2019;17:145-55. DOI: 10.1007/s10311-018-0785-9.
  • [5] Chai WS, Cheun JY, Kumar PS. A review on conventional and novel materials towards heavy metal adsorption in wastewater treatment application. J Cleaner Prod. 2021;296:126589. DOI: 10.1016/j.jclepro.2021.126589.
  • [6] Van DR, Benedetti L, De JJ. Performance evaluation of a smart buffer control at a wastewater treatment plant. Water Res. 2017;125:180-90. DOI: 10.1016/j.watres.2017.08.042.
  • [7] Vilanova R, Katebi R, Alfaro V. Multi-loop PI-based control strategies for the activated sludge process. IEEE Conf Emerging Technol Factory Automation, Mallorca, Spain. 2009:1-8. DOI: 10.1109/etfa.2009.5347062.
  • [8] Han Y, Brdys MA, Piotrowski R. Nonlinear PI control for dissolved oxygen tracking at wastewater treatment plant. IFAC Proc Volumes. 2008;41(2):13587-92. DOI: 10.3182/20080706-5-kr-1001.02301.
  • [9] Samsudin SI, Rahmat MF, Wahab NA. Improvement of activated sludge process using enhanced nonlinear PI controller. Arabian J Sci Eng. 2014;39(8):6575-86. DOI: 10.1007/s13369-014-1285-2.
  • [10] Liu X, Yu W. Research of dissolved oxygen concentration control strategy based on the fuzzy self-tuning PID parameter. IEEE Conf Control Decision, Chongqing, China. 2017;5928-32. DOI: 10.1109/ccdc.2017.7978229.
  • [11] Wahab NA, Katebi R, Balderud J. Multivariable PID control design for activated sludge process with nitrification and denitrification. Biochem Eng J. 2009;45(3):239-48. DOI: 10.1016/j.bej.2009.04.016.
  • [12] Ye HT, Li ZQ, Luo WG. Dissolved oxygen control of the activated sludge wastewater treatment process using adaptive fuzzy PID control. Conf Control, Xi'an, China. 2013;7510-3. DOI: 10.1016/j.compchemeng.2011.09.011.
  • [13] Kroll S, Dirckx G, Donckels BMR. Modelling real-time control of WWTP influent flow under data scarcity. Water Sci Technol. 2016;73(7):1637-43. DOI: 10.2166/wst.2015.64.1.
  • [14] Hernández-del-Olmo F, Gaudioso E, Duro N. Machine learning weather soft-sensor for advanced control of wastewater treatment plants. Sensors. 2019;19(14):3139. DOI: 10.3390/s19143139.
  • [15] Nguyen AT, Taniguchi T, Eciolaza Ll. Fuzzy control systems: Past, present and future. IEEE Computat Intelligence Magaz. 2019;14(1):56-68. DOI: 10.1109/MCI.2018.2881644.
  • [16] Wang CH, Kim J, Malgras V, Na J, Lin JJ, You J, et al. Metal-organic frameworks and their derived materials: emerging catalysts for a sulfate radicals‐based advanced oxidation process in water purification. Small. 2019;15(16):1900744. DOI: 10.1002/smll.201900744.
  • [17] Cheng PP, Jin Q, Jiang H, Hua M, Ye Z. Efficiency assessment of rural domestic sewage treatment facilities by a slacked-based DEA model. J Cleaner Prod. 2020;267:122111. DOI: 10.1016/j.jclepro.2020.122111.
  • [18] Wu HP, Gao XF, Wu M, Zhu Y, Xiong RW, Ye SJ. The efficiency and risk to groundwater of constructed wetland system for domestic sewage treatment-A case study in Xiantao, China. J Cleaner Prod. 2020;277:123384. DOI: 10.1016/j.jclepro.2020.123384.
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-30c11937-e576-4750-8d47-cc7d8f8f0705
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