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[1]劉圣譽,李彭,何義亮,等.基于人工神經網絡的反硝化濾池外碳源投加控制[J].中國給水排水,2020,36(7):19-25.
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基于人工神經網絡的反硝化濾池外碳源投加控制
中國給水排水[ISSN:1000-4062/CN:12-1073/TU] 卷: 第36卷 期數(shù): 2020年第7期 頁碼: 19-25 欄目: 出版日期: 2020-04-01
Title:External Carbon Source Dosage Control in Denitrification Biofilter Based on Artificial Neural Network
作者:劉圣譽1,2，李彭1,2，何義亮1,2，邵嘉慧2，任龍飛2
關鍵詞:反硝化濾池; 深度脫氮; 外碳源; 人工神經網絡
Keywords:denitrification biofilter; advanced nitrogen removal; external carbon source; artificial neural network
摘要:針對反硝化濾池外碳源過量投加導致的出水總碳超標與碳源浪費問題，利用實際污水與小試裝置研究了最適外碳源投加量的影響因素，并應用人工神經網絡建立了外碳源投加模型與脫氮效果預測模型。結果表明，基于進水總氮負荷與碳氮生化反應計量守恒而進行的外碳源投加可緩解碳源浪費與污染問題，但脫氮效果缺乏穩(wěn)定性，可考慮通過進水ORP、pH值、DO與溫度的綜合影響來進行改進。應用自適應學習速率動量梯度下降法建立了輸入為5項進水指標、輸出為最適投加量的外碳源投加模型，相關系數(shù)為0.964 8，表明模型中進水參數(shù)與最適投加量具有很好的相關性，外碳源投加模型的改進具有可行性。應用貝葉斯正則化法建立了輸入為5項進水指標、輸出為NO3- -N與NO2- -N濃度的脫氮效果預測模型，相關系數(shù)為0.908 5，表明預測反硝化濾池的脫氮效果具有一定可行性。外碳源投加模型可配合脫氮效果預測模型構建反硝化濾池外碳源投加控制系統(tǒng)，完善污水廠的自動化控制。
Abstract:Excessive dosage of carbon source in the denitrification biofilter will result in total carbon over set standard in the effluent and waste of carbon source.Therefore, factors influencing the optimal dosage of external carbon source were explored in the laboratory test device feeding actual sewage, and the models of external carbon source dosage and denitrification performance prediction were built by applying artificial neural network.The problem of waste and pollution of carbon source could be alleviated by adding external carbon sources based on the total nitrogen load of influent and the conservation of carbon nitrogen biochemical reaction. However, the denitrification performance was not stable, and it could be improved by the combined effects of ORP, pH, DO and temperature. The adaptive learning rate momentum gradient descent algorithm was used to establish a carbon source dosage model with input of five influent indexes and output of an optimal dosage of external carbon source. The correlation coefficient was 0.964 8,indicating that there was a good correlation between the influent parameters and the optimal carbon dosage and the improvement of the model was feasible. The Bayesian-regularization algorithm was used to establish the denitrification performance prediction model with input of five influent indexes and output of NO3- -N and NO2- -N concentration.The correlation coefficient was 0.908 5, indicating that it was feasible to predict the performance of the denitrification biofilter. The external carbon source dosage control system of denitrification biofilter could be established by cooperation of the carbon source dosage model and the denitrification performance prediction model, in order to improve the automatic control of the sewage treatment plant.
相似文獻/References:
[1]隋克儉,李家駒,孫永利,等.南方城鎮(zhèn)污水極限氮磷去除工藝中試研究[J].中國給水排水,2020,36(7):97.
[2]劉楊華,陳波,劉麗,等.MSBR與BAF工藝用于市政污水處理工程提標擴建[J].中國給水排水,2020,36(14):109.
LIU Yang-hua,CHEN Bo,LIU Li,et al.Application of MSBR and BAF Process in Upgrading and Expansion Project of Municipal Wastewater Treatment Plant[J].China Water & Wastewater,2020,36(7):109.
[3]錢夢潔,李興強,李軍.絲瓜絡和聚氨酯組合填料深度脫氮效果[J].中國給水排水,2020,36(15):73.
QIAN Meng-jie,LI Xing-qiang,LI Jun.Advanced Denitrification Efficiency of Loofah and Polyurethane Composite Filler[J].China Water & Wastewater,2020,36(7):73.
[4]栗文明,高敏,周軍,等.反硝化濾池污水處理工藝應用調研及設計要點[J].中國給水排水,2020,36(22):100.
LI Wen-ming,GAO Min,ZHOU Jun,et al.Application Survey and Design Points of the Denitrification Filter in Wastewater Treatment Process[J].China Water & Wastewater,2020,36(7):100.
[5]委燕,馬斌,許鑫鑫,等.厭氧氨氧化濾池的深度脫氮性能與菌群結構分析[J].中國給水排水,2021,37(9):15.
WEI Yan,MA Bin,XU Xin-xin,et al.Advanced Nitrogen Removal Performance and Microbial Community Composition of Anammox Biofilter[J].China Water & Wastewater,2021,37(7):15.
[6]楊清,郭淑琴,陳偉楠.準Ⅳ類出水標準下天津咸陽路污水處理廠的遷建提標設計[J].中國給水排水,2021,37(12):88.
YANG Qing,GUO Shu-qin,CHEN Wei-nan.Design of Relocation of Tianjin Xianyanglu Sewage Treatment Plant Upgraded to Quasi-Ⅳ Standard[J].China Water & Wastewater,2021,37(7):88.
[7]張玲玲,曹洋,顧淼,等.高排放標準下城市污水深度脫氮技術研究[J].中國給水排水,2021,37(13):27.
ZHANG Ling-ling,CAO Yang,GU Miao,et al.Advanced Nitrogen Removal Technology of Municipal Wastewater under High Discharge Standard[J].China Water & Wastewater,2021,37(7):27.
[8]李亮.MBBR在CAST工藝擴容提質工程中的應用[J].中國給水排水,2021,37(20):87.
LI Liang.Application of MBBR in CAST Process Expanding and Upgrading Project[J].China Water & Wastewater,2021,37(7):87.
更新日期/Last Update: 2020-04-01
中國給水排水雜志社官方網所有資料均源于網上的共享資源及
基于人工神經網絡的反硝化濾池外碳源投加控制
中國給水排水[ISSN:1000-4062/CN:12-1073/TU] 卷: 第36卷 期數(shù): 2020年第7期 頁碼: 19-25 欄目: 出版日期: 2020-04-01
- Title:
- External Carbon Source Dosage Control in Denitrification Biofilter Based on Artificial Neural Network
- Keywords:
- denitrification biofilter; advanced nitrogen removal; external carbon source; artificial neural network
- 摘要:
- 針對反硝化濾池外碳源過量投加導致的出水總碳超標與碳源浪費問題，利用實際污水與小試裝置研究了最適外碳源投加量的影響因素，并應用人工神經網絡建立了外碳源投加模型與脫氮效果預測模型。結果表明，基于進水總氮負荷與碳氮生化反應計量守恒而進行的外碳源投加可緩解碳源浪費與污染問題，但脫氮效果缺乏穩(wěn)定性，可考慮通過進水ORP、pH值、DO與溫度的綜合影響來進行改進。應用自適應學習速率動量梯度下降法建立了輸入為5項進水指標、輸出為最適投加量的外碳源投加模型，相關系數(shù)為0.964 8，表明模型中進水參數(shù)與最適投加量具有很好的相關性，外碳源投加模型的改進具有可行性。應用貝葉斯正則化法建立了輸入為5項進水指標、輸出為NO3- -N與NO2- -N濃度的脫氮效果預測模型，相關系數(shù)為0.908 5，表明預測反硝化濾池的脫氮效果具有一定可行性。外碳源投加模型可配合脫氮效果預測模型構建反硝化濾池外碳源投加控制系統(tǒng)，完善污水廠的自動化控制。
Abstract:- Excessive dosage of carbon source in the denitrification biofilter will result in total carbon over set standard in the effluent and waste of carbon source.Therefore, factors influencing the optimal dosage of external carbon source were explored in the laboratory test device feeding actual sewage, and the models of external carbon source dosage and denitrification performance prediction were built by applying artificial neural network.The problem of waste and pollution of carbon source could be alleviated by adding external carbon sources based on the total nitrogen load of influent and the conservation of carbon nitrogen biochemical reaction. However, the denitrification performance was not stable, and it could be improved by the combined effects of ORP, pH, DO and temperature. The adaptive learning rate momentum gradient descent algorithm was used to establish a carbon source dosage model with input of five influent indexes and output of an optimal dosage of external carbon source. The correlation coefficient was 0.964 8,indicating that there was a good correlation between the influent parameters and the optimal carbon dosage and the improvement of the model was feasible. The Bayesian-regularization algorithm was used to establish the denitrification performance prediction model with input of five influent indexes and output of NO3- -N and NO2- -N concentration.The correlation coefficient was 0.908 5, indicating that it was feasible to predict the performance of the denitrification biofilter. The external carbon source dosage control system of denitrification biofilter could be established by cooperation of the carbon source dosage model and the denitrification performance prediction model, in order to improve the automatic control of the sewage treatment plant.
相似文獻/References:
[1]隋克儉,李家駒,孫永利,等.南方城鎮(zhèn)污水極限氮磷去除工藝中試研究[J].中國給水排水,2020,36(7):97.
[2]劉楊華,陳波,劉麗,等.MSBR與BAF工藝用于市政污水處理工程提標擴建[J].中國給水排水,2020,36(14):109.
LIU Yang-hua,CHEN Bo,LIU Li,et al.Application of MSBR and BAF Process in Upgrading and Expansion Project of Municipal Wastewater Treatment Plant[J].China Water & Wastewater,2020,36(7):109.
[3]錢夢潔,李興強,李軍.絲瓜絡和聚氨酯組合填料深度脫氮效果[J].中國給水排水,2020,36(15):73.
QIAN Meng-jie,LI Xing-qiang,LI Jun.Advanced Denitrification Efficiency of Loofah and Polyurethane Composite Filler[J].China Water & Wastewater,2020,36(7):73.
[4]栗文明,高敏,周軍,等.反硝化濾池污水處理工藝應用調研及設計要點[J].中國給水排水,2020,36(22):100.
LI Wen-ming,GAO Min,ZHOU Jun,et al.Application Survey and Design Points of the Denitrification Filter in Wastewater Treatment Process[J].China Water & Wastewater,2020,36(7):100.
[5]委燕,馬斌,許鑫鑫,等.厭氧氨氧化濾池的深度脫氮性能與菌群結構分析[J].中國給水排水,2021,37(9):15.
WEI Yan,MA Bin,XU Xin-xin,et al.Advanced Nitrogen Removal Performance and Microbial Community Composition of Anammox Biofilter[J].China Water & Wastewater,2021,37(7):15.
[6]楊清,郭淑琴,陳偉楠.準Ⅳ類出水標準下天津咸陽路污水處理廠的遷建提標設計[J].中國給水排水,2021,37(12):88.
YANG Qing,GUO Shu-qin,CHEN Wei-nan.Design of Relocation of Tianjin Xianyanglu Sewage Treatment Plant Upgraded to Quasi-Ⅳ Standard[J].China Water & Wastewater,2021,37(7):88.
[7]張玲玲,曹洋,顧淼,等.高排放標準下城市污水深度脫氮技術研究[J].中國給水排水,2021,37(13):27.
ZHANG Ling-ling,CAO Yang,GU Miao,et al.Advanced Nitrogen Removal Technology of Municipal Wastewater under High Discharge Standard[J].China Water & Wastewater,2021,37(7):27.
[8]李亮.MBBR在CAST工藝擴容提質工程中的應用[J].中國給水排水,2021,37(20):87.
LI Liang.Application of MBBR in CAST Process Expanding and Upgrading Project[J].China Water & Wastewater,2021,37(7):87.
更新日期/Last Update: 2020-04-01
