TY - JOUR
T1 - Formal verification of wastewater treatment processes using events detected from continuous signals by means of artificial neural networks. Case study
T2 - SBR plant
AU - Luccarini, Luca
AU - Bragadin, Gianni Luigi
AU - Colombini, Gabriele
AU - Mancini, Maurizio
AU - Mello, Paola
AU - Montali, Marco
AU - Sottara, Davide
PY - 2010/5
Y1 - 2010/5
N2 - 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.
AB - 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.
KW - Artificial neural networks
KW - Business process management
KW - Event detection
KW - Intelligent systems
KW - Rule-based management system
KW - SBR
UR - http://www.scopus.com/inward/record.url?scp=75149198666&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=75149198666&partnerID=8YFLogxK
U2 - 10.1016/j.envsoft.2009.05.013
DO - 10.1016/j.envsoft.2009.05.013
M3 - Article
AN - SCOPUS:75149198666
SN - 1364-8152
VL - 25
SP - 648
EP - 660
JO - Environmental Modelling and Software
JF - Environmental Modelling and Software
IS - 5
ER -