Formal verification of wastewater treatment processes using events detected from continuous signals by means of artificial neural networks: Case study: SBR plant
MetadataShow full item record
SubjectBusiness process management; Event detection; Artificial neural networks; Intelligent systems; Rule-based management system; SBR
This paper proposes a modular architecture for the analysis and the validation of wastewater treatment processes. An algorithm using neural networks is used to extract the relevant qualitative patterns, such as apexes, knees and steps, from the signals acquired in the reaction tanks. These patterns, which show changes in the signals trend, are mapped to events in the process and logged using an appropriate XML format. The logs, in turn, are considered traces of the execution of a manufacturing process and validated using tools commonly applied for the Verification of Business Processes. The system has been applied to the data collected from a Sequencing Batch Reactor (SBR) for municipal wastewater treatment, equipped with probes for the on-line acquisition of signals such as pH, oxidation--reduction potential (ORP) and dissolved oxygen (DO). A SBR has turned out to be a suitable case study since the commonly acknowledged criteria for monitoring the biological processes (nitrification and denitrification) can be expressed in the form or qualitative constraints, which are easily translated into formal rules. The process logs, hence, are matched against these rules, which act as filters and quality classifiers.
Showing items related by title, author, creator and subject.
Formal verification of wastewater treatment processes using events detected from continuous signals by means of artificial neural networks. Case study: SBR plant Luccarini L; Bragadin GL; Colombini G; Mancini M; Mello P; Montali M; Sottara D (Elsevier, 2010)This paper proposes a modular architecture for the analysis and the validation of wastewater treatment processes. An algorithm using neural networks is used to extract the relevant qualitative patterns, such as "apexes", ...
A general methodology for performance prediction of pumps-as-turbines using Artificial Neural Networks Rossi M; Renzi M (2018)Artificial Neural Networks (ANNs) are used in this work as a computational methodology to forecast both Best Efficiency Point (BEP) and performance curves of Pumps-as-Turbines (PATs) operating in reverse mode. Experimental ...
Local reflections on low-carbon energy systems: A systematic review of actors, processes, and networks of local societies Balest J; Pisani E; Vettorato D; Secco L (2018)Local population actions determine the level of renewability of local energy systems in the context of energy transition goals. Local population makes energy choices based on the availability of different territorial ...