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Numrering	Referens	Omslagsbild	Hitta
1.	Marais, Heidi Lynn, 1996-, et al. (författare) Detectability of Fault Signatures in a Wastewater Treatment Process 2021 Ingår i: Proceedings of The First SIMS EUROSIM Conference on Modelling and Simulation, SIMS EUROSIM 2021, and 62nd International Conference of Scandinavian Simulation Society, SIMS 2021. - : Scandinavian Simulation Society and Linköping University Electronic Press. - 9789179292195 ; , s. 418-423 Konferensbidrag (refereegranskat)abstract In a wastewater treatment plant reliable fault detection is an integral component of process supervision and ensuring safe operation of the process. Detecting and isolating process faults requires that sensors in the process can be used to uniquely identify such faults. However, sensors in the wastewater treatment process operate in hostile environments and often require expensive equipment and maintenance. This work addresses this problem by identifying a minimal set of sensors which can detect and isolate these faults in the Benchmark Simulation Model No. 1.Residual-based fault signatures are used to determine this sensor set using a graph-based approach; these fault signatures can be used in future work developing fault detection methods. It is recommended that further work investigate what sizes of faults are critical to detect based on their potential effects on the process, as well as ways to select an optimal sensor set from multiple valid configurations.

Marais, Heidi Lynn, 1996-, et al. (författare)
Detectability of Fault Signatures in a Wastewater Treatment Process
2021
Ingår i: Proceedings of The First SIMS EUROSIM Conference on Modelling and Simulation, SIMS EUROSIM 2021, and 62nd International Conference of Scandinavian Simulation Society, SIMS 2021. - : Scandinavian Simulation Society and Linköping University Electronic Press. - 9789179292195 ; , s. 418-423
Konferensbidrag (refereegranskat)abstract
- In a wastewater treatment plant reliable fault detection is an integral component of process supervision and ensuring safe operation of the process. Detecting and isolating process faults requires that sensors in the process can be used to uniquely identify such faults. However, sensors in the wastewater treatment process operate in hostile environments and often require expensive equipment and maintenance. This work addresses this problem by identifying a minimal set of sensors which can detect and isolate these faults in the Benchmark Simulation Model No. 1.Residual-based fault signatures are used to determine this sensor set using a graph-based approach; these fault signatures can be used in future work developing fault detection methods. It is recommended that further work investigate what sizes of faults are critical to detect based on their potential effects on the process, as well as ways to select an optimal sensor set from multiple valid configurations.

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