Fault detection with moving window PCA using NIRS spectra for monitoring the anaerobic digestion process.

Principal component analysis (PCA) is a popular method for process monitoring. However, most processes are time-varying, thus older samples are not representative of the current process status. This led to the introduction of adaptive-PCA based monitoring, such as moving window PCA (MWPCA). In this study, near-infrared spectroscopy (NIRS) responses to digester failures were evaluated to develop a spectral data processing tool. Tests were performed with a spectroscopic probe (350-2,500 nm), using a 35 L mesophilic continuously stirred tank reactor. Co-digestion experiments were performed with pig slurry mixed with several co-substrates. Different stresses were induced by abruptly increasing the organic load rate, changing the feedstock or stopping the stirring. Physicochemical parameters as well as NIRS spectra were acquired for lipid, organic and protein overloads experiments. MWPCA was then applied to the collected spectra for a multivariate statistical process control. MWPCA outputs, Hotelling T2 and residuals Q statistics showed that most of the induced dysfunctions can be detected with variations in these statistics according to a defined criterion based on spectroscopic principles and the process. MWPCA appears to be a multivariate statistical method that could help in decision support in industrial biogas plants.

Detection of early imbalances in semi-continuous anaerobic co-digestion process based on instantaneous biogas production rate.

The aim of this study was to investigate the use of biogas production rate kinetics for the monitoring of anaerobic co-digestion. Recent extensive studies of degradation pathways showed that acetoclastic methanogenesis is not always the main pathway. Hydrogenotrophic methanogenesis and syntrophic acetate oxidation can also dominate, mostly for operating conditions with high concentrations of ammonia or volatile fatty acids … These conditions are also known to cause instability in the digester's operation especially in co-digestion due to substrate variability. Therefore, co-digestion experiments were conducted with several co-substrates using a continuously stirred 35-L tank reactor. Degradation pathways and their potential shifts were identified by monitoring variations in biogas production rate kinetics using a principal component analysis model. The shifts in the degradation pathways were used to monitor the process. These shift points were found to provide early warnings of instabilities in the anaerobic co-digestion process.

Data on near infrared polarization spectroscopy measurements to evaluate the potential of the Mueller matrix elements in characterization of turbid liquid samples.

In this article, a set of 50 turbid liquid samples with different levels of absorption and scattering properties were prepared and measured at various orientations of polarizers and analyzers to obtain the 16 elements of the complete Muller matrix. Partial Least Square (PLS) was used to build calibration models in order to assess the potential of polarization spectroscopy through the elements of Muller matrix to predict chemical and physical parameters.

Dataset of near infrared spectroscopy measurements to predict rheological parameters of sludge.

In the dataset presented in this article, 36 sludge samples were characterized. Rheological parameters were determined and near infrared spectroscopy measurements were realized. In order to assess the potential of near infrared spectroscopy to predict rheological parameters of sludge, Partial Least Square algorithm was used to build calibration models.