A filtering algorithm for high-resolution flow traces to improve water end-use analysis
| Autor: | Francisco J. Arregui, R. Cobacho, L. Pastor-Jabaloyes |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Water micro-component
INGENIERIA HIDRAULICA Computer science 0207 environmental engineering 02 engineering and technology 010501 environmental sciences 01 natural sciences Signal Distortion Metre Water end use event 020701 environmental engineering 0105 earth and related environmental sciences Water Science and Technology Noise (signal processing) MECANICA DE FLUIDOS Residential water flow trace disaggregation 6. Clean water Identification (information) Statistical classification Data point Flow (mathematics) 13. Climate action Smart metering data Filtering Algorithm |
| Zdroj: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia instname |
| DOI: | 10.2166/ws.2018.090 |
| Popis: | [EN] One of the main difficulties encountered when designing automatic tools for water end use identification is the inherent noise present in recorded flow traces. Noise is mainly caused by the inability of the monitoring equipment to accurately register water consumption and data-loggers to register, without distortion, the signal received from the water meter. A universal filtering algorithm has been developed to remove noise and simplify water consumption flow traces with the aim of improving future automatic end use identification algorithms. The performance of the proposed filtering methodology is assessed through the analysis of 21,647 events. Water consumption data were sourced from two different water end use studies, having consumers and monitoring equipment with dissimilar characteristics. The results obtained show that the algorithm is capable of removing an average of 70% of the data points that constitute the flow traces of the complex events examined. The simplified flow traces allow for faster and more accurate disaggregation and classification algorithms, without losing significant information or distorting the original signal. The ability of the proposed filtering algorithm to fit the original flow traces was benchmarked using the Kling-Gupta efficiency coefficient, obtaining an average value above 0.79. This study has received funding by the IMPADAPT project/CGL2013-48424-C2-1-R from the Spanish ministry MINECO with European FEDER funds and from the European Union's Seventh Framework Programme (FP7/2007e2013) under grant agreement no. 619172 (SmartH2O: an ICT Platform to Leverage on Social Computing for the Efficient Management of Water Consumption). |
| Databáze: | OpenAIRE |
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