Evaluation of near infrared spectroscopy and software sensor methods for determination of total alkalinity in anaerobic digesters

被引:25
作者
Ward, Alastair J. [1 ]
Hobbs, Philip J.
Holliman, Peter J. [2 ]
Jones, David L. [3 ]
机构
[1] Univ Aarhus, Fac Agr Sci, Dept Biosyst Engn, DK-8830 Tjele, Denmark
[2] N Wyke Res, N Wyke Res Stn, Okehampton EX20 2SB, Devon, England
[3] Bangor Univ, Sch Environm Nat Resources & Geog, Bangor LL57 2UW, Gwynedd, Wales
基金
英国生物技术与生命科学研究理事会;
关键词
Biogas; Anaerobic digestion; Monitoring; NIRS; Software sensor; DIFFUSE-REFLECTANCE SPECTROSCOPY; FLUIDIZED-BED REACTOR; WASTE-WATER; PERFORMANCE; MONITOR; PROTEIN;
D O I
10.1016/j.biortech.2010.12.046
中图分类号
S2 [农业工程];
学科分类号
0828 ;
摘要
In this study two approaches to predict the total alkalinity (expressed as mg L-1 HCO3-) of an anaerobic digester are examined: firstly, software sensors based on multiple linear regression algorithms using data from pH, redox potential and electrical conductivity and secondly, near infrared reflectance spectroscopy (NIRS). Of the software sensors, the model using data from all three probes but a smaller dataset using total alkalinity values below 6000 mg L-1 HCO3- produced the best calibration model (R-2 = 0.76 and root mean square error of prediction (RMSEP) of 969 mg L-1 HCO3-). When validated with new data, the NIRS method produced the best model (R-2 = 0.87 RMSEP = 1230 mg L-1 HCO3-). The NIRS sensor correlated better with new data (R-2 = 0.54). In conclusion, this study has developed new and improved algorithms for monitoring total alkalinity within anaerobic digestion systems which will facilitate real-time optimisation of methane production. (C) 2010 Elsevier Ltd. All rights reserved.
引用
收藏
页码:4083 / 4090
页数:8
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