Data-driven fault detection methods for detecting small-magnitude faults in anaerobic digestion process.

Early detection of small-magnitude faults in anaerobic digestion (AD) processes is a mandatory step for preventing serious consequence in the future. Since volatile fatty acids (VFA) accumulation is widely suggested as a process health indicator, a VFA soft-sensor was developed based on support vector machine (SVM) and used for generating the residuals by comparing real and predicted VFA. The estimated residual signal was applied to univariate statistical control charts such as cumulative sum (CUSUM) and square prediction error (SPE) to detect the faults. A principal component analysis (PCA) model was also developed for comparison with the aforementioned approach. The proposed framework showed excellent performance for detecting small-magnitude faults in the state parameters of AD processes.

Fault detection and diagnosis in water resource recovery facilities using incremental PCA.

Because of the static nature of conventional principal component analysis (PCA), natural process variations may be interpreted as faults when it is applied to processes with time-varying behavior. In this paper, therefore, we propose a complete adaptive process monitoring framework based on incremental principal component analysis (IPCA). This framework updates the eigenspace by incrementing new data to the PCA at a low computational cost. Moreover, the contribution of variables is recursively provided using complete decomposition contribution (CDC). To impute missing values, the empirical best linear unbiased prediction (EBLUP) method is incorporated into this framework. The effectiveness of this framework is evaluated using benchmark simulation model No. 2 (BSM2). Our simulation results show the ability of the proposed approach to distinguish between time-varying behavior and faulty events while correctly isolating the sensor faults even when these faults are relatively small.

Separation of cellulose from industrial paper mill wastewater dried sludge using a commercial and cheap ionic liquid.

Industrial wastewaters and their treatment are now placed at the heart of the environmental concerns that industries face. Some research work has been carried out in order to limit the impact of these wastes on the environment as well as their costs. In this study, wastewater dehydrated sludge (55% wt. water content) from the paper industry was used to recover cellulose by using tetrakis(hydroxymethyl)phosphonium chloride, [P(CH2OH)4]Cl, ionic liquid as a solvent. The ionic liquid has shown remarkable results in terms of cellulose extraction in addition to its non-volatility and lower toxicity compared to organic volatile solvents. All cellulose, based on dry sludge, was recovered from the industrial dehydrated sludge with better operation conditions. The influence of temperature and the quantity of ionic liquid was preliminary studied in order to optimise the extraction conditions.

Compact Carbon-Based Membrane Reactors for the Intensified Anaerobic Decolorization of Dye Effluents.

Carbon-based membranes integrated with anaerobic biodegradation are presented as a unique wastewater treatment approach to deal with dye effluents. This study explores the scope of ceramic-supported carbon membrane bioreactors (B-CSCM) and ceramic-supported graphene oxide membrane bioreactors (B-CSGOM) to decolorize azo dye mixtures (ADM) and other dyes. The mixture was prepared using an equimolar composition of monoazo Acid Orange 7, diazo Reactive Black 5, and triazo Direct Blue 71 dye aqueous solution. Afterwards, as in the ADM experiment, both compact units were investigated for their ability in the biodecolorization of Methylene Blue (MB) and Rhodamine B (RhB) dye solutions, which do not belong to the azo family. The obtained outcomes revealed that the conductive surface of the graphene oxide (GO) membrane resulted in a more efficient and higher color removal of all dye solutions than B-CSCM under a wide feed concentration and permeate flux ranges. The maximum color removal at low feed concentration (50 mg·L-1) and permeate flux (0.05 L·m-2·h-1) was 96% for ADM, 98% for MB and 94% for RhB, whereas it was 89%, 94% and 66%, respectively, for B-CSCM. This suggests that the robust, cost-effective, efficient nanostructures of B-CSGOM can successfully remove diverse azo dye solutions from wastewater better than the B-CSCM does.

Degradation of dibenzothiophene by Pseudomonas putida.

The microbial degradation of dibenzothiophene (DBT) and other organosulphur compounds such as thiophene-2-carboxylate (T2C) is of interest for the potential desulphurization of coal. The feasibility of degradation of DBT and T2C by Pseudomonas putida and other bacteria was analysed. Pseudomonas putida oxidized sulphur from DBT in the presence of yeast extract, but it did not when DBT was the sole source of carbon.