TY - JOUR
T1 - Estimation of Acetic Acid Concentration from Biogas Samples Using Machine Learning
AU - Putra, Lingga Aksara
AU - Huber, Bernhard
AU - Gaderer, Matthias
N1 - Publisher Copyright:
© 2023 Lingga Aksara Putra et al.
PY - 2023
Y1 - 2023
N2 - In a biogas plant, the acetic acid concentration is a major component of the substrate as it determines the pH value, and this pH value correlates with the volume of biogas produced. Since it requires specialized laboratory equipment, the concentration of acetic acid in a biogas substrate cannot be measured on-line. The project aims to use NIR sensors and machine learning algorithms to estimate the acetic acid concentration in a biogas substrate based on the measured intensities of the substrate. As a result of this project, it was possible to determine whether the acetic acid concentration in a biogas substrate is higher or lower than 2 g/l using machine learning models.
AB - In a biogas plant, the acetic acid concentration is a major component of the substrate as it determines the pH value, and this pH value correlates with the volume of biogas produced. Since it requires specialized laboratory equipment, the concentration of acetic acid in a biogas substrate cannot be measured on-line. The project aims to use NIR sensors and machine learning algorithms to estimate the acetic acid concentration in a biogas substrate based on the measured intensities of the substrate. As a result of this project, it was possible to determine whether the acetic acid concentration in a biogas substrate is higher or lower than 2 g/l using machine learning models.
UR - http://www.scopus.com/inward/record.url?scp=85149438271&partnerID=8YFLogxK
U2 - 10.1155/2023/2871769
DO - 10.1155/2023/2871769
M3 - Article
AN - SCOPUS:85149438271
SN - 1687-806X
VL - 2023
JO - International Journal of Chemical Engineering
JF - International Journal of Chemical Engineering
M1 - 2871769
ER -