Improved Monitoring Of Anaerobic Digestion Processes Using Principal Component Analysis And Control Charts
An interesting and innovated alternative to handle anaerobic digestion (AD) data resides in multivariate statistical approaches since a more accuracy analysis can be performed and fault or abnormal schemes detections can be enhanced.In this paper,principal component analysis (PCA) was the basic multivariate tool used to compare single and two stage AD process performances when treating waste activated sludge (WAS),in order to improve their monitoring and control.Two experiments designed single and two-stage AD using WAS and fermented WAS as substrates in order to compare the current results with outcomes of a univariated analysis.Findings from the principal component analysis (PCA) model agreed with results from the univariate data analysis but additionally showed a higher variability and changes on the stability trend in the AD of WAS.Besides,multivariate statistical process control (MSPC) using Shewhart control charts combined with PCA displayed an out-of-control scheme revealing a transition period,in which the stability pattern of this experiment changed strongly,towards an accumulation of volatile fatty acids.
Anaerobic digestion improved monitoring principal component analysis control charts
W.R.M.Leite P.Belli Filho M.Gottardo P.Pavan D.Bolzonella
Department of Civil and Environmental Engineering, Federal University of Pernambuco, Recife, Brazil Department of Sanitary and Environmental Engineering, Federal University of Santa Catarina, Trindade Department of Informatics, Statistic and Environmental Science, University Ca Foscari of Venice, Ven Dcpartment of Biotechnology, University of Verona, Strada Le Grazie 15.37134 Verona, Italy
国际会议
The 15th IWA World Conference on Anaerobic Digestion( 第15届IWA世界厌氧大会)
北京
英文
398-402
2017-10-17（万方平台首次上网日期，不代表论文的发表时间）