Eugenio F. Carrasco

Rule-based diagnosis and supervision of a pilot-scale wastewater treatment plant using fuzzy logic techniques

Abstract This paper is focused on the development of a fuzzy expert system capable to diagnose the state of a pilot-scale wastewater treatment plant, its trend and also to be able to decide the best commands to be sent to the final control elements to recover the stable operation in case of disturbances. The development of the fuzzy expert system was carried out by selecting the on-line variables to be used, building the fuzzy membership functions for each input and output variable and developing a knowledge based rules structure. Finally, the fuzzy expert system was carefully tested and adjusted by performing some experiments.

Diagnosis of acidification states in an anaerobic wastewater treatment plant using a fuzzy-based expert system

Abstract A fuzzy-logic-based diagnosis system for the determination of acidification states on an anaerobic wastewater treatment plant was developed. The diagnosis system uses experts’ knowledge to determine the acidification state of the process. The information of several on-line measured variables, which are classified under linguistic labels, and the expert knowledge are implemented by means of a fuzzy-based rules structure. The acidification state of the system within the anaerobic reactor is determined by means of evaluating the fuzzy inference system for the given inputs. A representative experiment of application of the developed diagnosis system to a progressive acidification caused by a hydraulic overload in the digester is presented and discussed.

Application of fuzzy logic for the integration of environmental criteria in ecodesign

The ecodesign of a product implies that different potential environmental problems of diverse nature must be considered, apart from the general design criteria (i.e., technical, functional, ergonomic, aesthetic or economical). In this sense, an ecodesign tool integrating the criteria provided by three environmental evaluation methodologies, namely Ecological Footprint (EF), Life Cycle Assessment (LCA) and Environmental Risk Assessment (ERA), has been constructed on the basis of fuzzy logic reasoning and features. This idea enabled the decision making at process and product level taking into account the values of the different indicators at a time. The relative importance of each of them has been established through the definition of membership functions as inputs to the fuzzy inference reasoning procedure in the case of a specific product. As a result, a Fuzzy EcoDesign Index (FEcoDI) was obtained. A well known case study was used to test the tool. Different packaging materials for a beverage bottle were considered to identify the most environmentally friendly option.

Advanced Monitoring and Supervision of Biological Treatment of Complex Dairy Effluents in a Full-Scale Plant

The operation of a wastewater treatment plant treating effluents from a dairy laboratory was monitored by an advanced system. This plant comprises a 12 m3 anaerobic filter (AF) reactor and a 28 m3 sequential batch reactor (SBR) coupled in series and is equipped with the following on‐line measurement devices: biogas flow meter, feed and recycling flow meters, temperature sensor, dissolved oxygen analyzer, and redox meter. Other parameters such as chemical oxygen demand (COD), volatile fatty acids (VFA), etc. were determined off‐line. The plant has been in operation for 634 days, the influent flow rate being 6–8 m3/d. COD concentration of the influent ranged between 8 and 12 kg COD/m3, resulting in COD values in the effluent around 50–200 mg/L. The behavior of the system was studied using the set of measurements collected by the data acquisition program especially developed for this purpose. Monitoring of variables such as anaerobic reactor temperature permitted the detection and prevention of several failures such as temperature shocks in the AF reactor. Besides, off‐line measurements such as the alkalinity or the VFA content, together with the on‐line measurements, provided immediate information about the state of the plant and the detection of several anomalies, such as organic overloads in the SBR, allowing the implementation of several fast control actions.

Development of a Fuzzy-Based Diagnosis System for the Supervision of the Operation in Anaerobic Wastewater Treatment Plants

Abstract A fuzzy logic based diagnosis system for the supervision of the operation of a wastewater treatment plant was developed. The diagnosis system uses the experts’ knowledge to determine the state of the process, using several measured variables, by means of a base of rules. The system allows to know the acidification state in the reactor by using fuzzy inference system evaluations for given inputs and with variables quantified using linguistic labels. A representative experiment of an acidification of the anaerobic reactor due to a hydraulic overload, together with the fuzzy diagnosis system responses, are presented.

Optimization under fuzzy if-then rules using stochastic algorithms

Abstract A new approach to optimization of processes described by fuzzy rules, in which the functional relationship between the decision variables and the objective function is not completely known, is introduced in this paper. It is based on stochastic algorithms and allows to determine optimal values of state variables and to optimize fuzzy rules (parameters of membership functions). Stochastic algorithms have many advantages like their robustness and, in most cases, global convergence properties. Here, a new algorithm (FICRS) was developed, being applied to the solution of a case stdy taken from the recent literature.