Evaluation of artificial neural network models for online monitoring of alkalinity in anaerobic co-digestion system
作者: Xuemei WangXue BaiZifu LiXiaoqin ZhouShikun ChengJiachen SunTing Liu
作者单位: 1School of Energy and Environmental Engineering, Beijing Key Laboratory of Resource-oriented Treatment of Industrial Pollutants, International Science and Technology Cooperation Base for Environmental and Energy Technology of MOST, University of Science and Technology Beijing, Beijing 100083, PR China
刊名: Biochemical Engineering Journal, 2018
来源数据库: Elsevier Journal
DOI: 10.1016/j.bej.2018.09.010
关键词: Anaerobic co-digestionAlkalinityOnline monitoringArtificial neural networkSoft sensor methodMathematical modeling
原始语种摘要: Abstract(#br)Compared to pH monitoring during the anaerobic digestion process, alkalinity as an indicator could provide earlier warning for instability of digestion process, which is very important for efficient operation of biogas digesters, especially for multiple feeding substances. However, the online monitoring of alkalinity is still unavailable until now. In this study, available online measured parameters such as pH, oxidation and reduction potential (ORP), and electrical conductivity were selected as inputs, and the soft sensor method based on artificial neural network (ANN) was applied for alkalinity modeling to develop an online monitoring strategy. The dataset was obtained from a 6 month continuously operating anaerobic co-digestion system of cow manure, corn straw, and fruit...
全文获取路径: Elsevier  (合作)
影响因子:2.579 (2012)

  • alkalinity 碱度
  • anaerobic 嫌气的
  • digestion 消化
  • monitoring 监视
  • online 联机
  • ORP Orbital Rendezvous Procedure
  • artificial 人为的
  • neural 神经系统的
  • oxidation 氧化
  • strategy 战略