A methodology and a software tool for sensor data validation/reconstruction : application to the Catalonia regional water network
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In this paper, a sensor data validation/reconstruction methodology applicable to water networks and its implementation by means of a software tool are presented. The aim is to guarantee that the sensor data are reliable and complete in case that sensor faults occur. The availability of such dataset is of paramount importance in order to successfully use the sensor data for further tasks e.g. water billing, network efficiency assessment, leak localization and real-time operational control. The methodology presented here is based on a sequence of tests and on the combined use of spatial models (SM) and time series models (TSM) applied to the sensors used for real-time monitoring and control of the water network. Spatial models take advantage of the physical relations between different system variables (e.g. flow and level sensors in hydraulic systems) while time series models take advantage of the temporal redundancy of the measured variables (here by means of a Holt–Winters (HW) time series model). First, the data validation approach, based on several tests of different complexity, is described to detect potential invalid or missing data. Then, the reconstruction process is based on a set of spatial and time series models used to reconstruct the missing/invalid data with the model estimation providing the best fit. A software tool implementing the proposed data validation and reconstruction methodology is also described. Finally, results obtained applying the proposed methodology to a real case study based on the Catalonia regional water network is used to illustrate its performance.
CitacióCuguero-Escofet, M.A., García, D., Quevedo, J., Puig, V., Espin, S., Roquet, J. A methodology and a software tool for sensor data validation/reconstruction : application to the Catalonia regional water retwork. "Control engineering practice", 01 Abril 2016, vol. 49, p. 159-172.
Versió de l'editorhttp://www.sciencedirect.com/science/article/pii/S0967066115300459