Title | ||
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Formal verification of wastewater treatment processes using events detected from continuous signals by means of artificial neural networks. Case study: SBR plant |
Abstract | ||
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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. |
Year | DOI | Venue |
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2010 | 10.1016/j.envsoft.2009.05.013 | Environmental Modelling and Software |
Keywords | Field | DocType |
biological process,event detection,business processes,wastewater treatment process,qualitative constraint,sequencing batch,artificial neural networks,intelligent systems,municipal wastewater treatment,rule-based management system,case study,artificial neural network,formal verification,sbr,manufacturing process,sbr plant,process log,relevant qualitative pattern,business process management,continuous signal,signals trend,rule based,management system,wastewater treatment | Data mining,Data collection,Business process management,XML,Business process,Intelligent decision support system,Computer science,Sequencing batch reactor,Artificial neural network,Management science,Environmental engineering,Formal verification | Journal |
Volume | Issue | ISSN |
25 | 5 | Environmental Modelling and Software |
Citations | PageRank | References |
8 | 0.77 | 13 |
Authors | ||
7 |
Name | Order | Citations | PageRank |
---|---|---|---|
Luca Luccarini | 1 | 10 | 1.95 |
Gianni Luigi Bragadin | 2 | 8 | 0.77 |
Gabriele Colombini | 3 | 9 | 1.50 |
Maurizio Mancini | 4 | 8 | 0.77 |
Paola Mello | 5 | 444 | 21.33 |
Marco Montali | 6 | 1280 | 99.36 |
Davide Sottara | 7 | 72 | 14.68 |