Validation and reconstruction of flow meter data in the Barcelona water distribution network

Control Engineering Practice

Volumn 18, Issue 6, 2010, Pages 640-651

  Quevedo, J ^a   Puig, V ^a   Cembrano, G ^a   Blanch, J ^a   Aguilar, J ^b   Saporta, D ^c   Benito, G ^d   Hedo, M ^d   Molina, A ^d  

^a INSTITUT DE ROBÒTICA I INFORMÀTICA INDUSTRIAL CSIC UPC   (Spain)

^b LAAS CNRS   (France)

^c AGBAR   (Spain)

^d Adasa Sistemas   (Spain)

Author keywords

Fault detection; Flow meter; Fuzzy logic classifier; Sensor failure; Telecontrol system; Water distribution network

Indexed keywords

BARCELONA; CORRELATION ANALYSIS; DEMAND PATTERN; FALSE DATA; FORECASTING MODELS; MODEL-BASED; SENSOR FAILURE; TELECONTROL SYSTEMS; TIME-SCALES; WATER DISTRIBUTION NETWORKS;

CLASSIFIERS; CORRELATION METHODS; DATA FLOW ANALYSIS; DISTRIBUTED PARAMETER NETWORKS; FAULT DETECTION; FLOW MEASUREMENT; FLOWMETERS; FUZZY LOGIC; FUZZY SYSTEMS; SENSORS; SIGNAL ANALYSIS; TIME SERIES; WATER SUPPLY;

WATER DISTRIBUTION SYSTEMS;

EID: 77953027264     PISSN: 09670661     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.conengprac.2010.03.003     Document Type: Article

References (43)

1. Alvisi S., Franchini M., Marinelli A. A short-term, pattern-based model for water-demand forecasting. Journal of Hydroinformatics 2007, 9(1).
2. Arteaga F, Ferrer A. Dealing with missing data in MSCP: Several methods, different interpretations, some examples. Journal of Chemometrics 2002, 16:408-418.
3. Abraham, B., Box, G. E. P. (1975). Linear models, time series and outliers. Technical report no. 438, Department of Statistics, University of Wisconsin-Madison.
4. Aguilar-Martin J., Lopez de Mantaras R. The process of classification and learning the meaning of linguistic descriptors of concepts, approximate reasoning in decision analysis 1982, North Holland Publishing Company, pp. 165-175.
5. Box, G. E. P., Jenkins, G. M. (1970). Time series analysis forecasting and control. Holden-Day.
6. Bennis S., Berrada F., Kang N. Improving single variable and multivariable techniques for estimating missing hydrological data. Journal of Hydrology 1997, 191(1-4):87-105.
7. Bennis S., Kang N. A new methodology for validating historical hydrometric data with redundant measurements. Hydraulic engineering software VIII 2000, WIT Press. W.R. Blain, C.A. Brebbia (Eds.).
8. Boukhris A., Giuliani S., Mourot G. Rainfall-runoff multi-modelling for sensor fault diagnosis. Control Engineering Practice 2001, 9(6):659-671.
9. Brdys M., Ulanicki B. Operational control of water systems: Structures, algorithms and applications 1994, Prentice Hall International.
10. Burnell, D. (2003). Auto-validation of district meter data. In C. Maksimovic, D. Butler, & F. A. Memon (Eds.), Advances in water supply management. The Netherlands: Swets & Zeitlinger Publishers.
11. Cembrano G., Wells G., Quevedo J., Pérez R., Argelaguet R. Optimal control of a water distribution network in a supervisory control system. Control Engineering Practice 2000, 8(10):1177-1188.
12. Ciavatta S., Pastres R., Lin Z., Beck M.B., Badetti C., Ferrari G. Fault detection in a real-time monitoring network for water quality in the lagoon of Venice (Italy). Water Science and Technology 2004, 50(11):51-58.
13. Crobeddu.E., Bennis S. Data acquisition, validation and forecasting for a combined sewer network. Waste management and the environment III 2006, WIT Press. V. Popov, A.G. Kungolos, C.A. Brebbia, H. Itoh (Eds.).
14. Denoeux, T., Boudaoud, N., Canu, S., Dang, V. M., Govaert, G., Masson, M., Petitrenaud, S., Soltani, S. (1997). High level data fusion methods. Technical report CNRS/EM2S/330/11-97v1.0, Université de Technologie de Compiègne, Compiègne, France, November 1997.
15. Hamioud, F., Joannis, C., Ragot, J. (2005a). Fault diagnosis for validation of hydrometric data collected from sewer networks. In Proceedings of the 10th international conference on urban drainage, 10ICUD, Copenhagen, Denmark, August 21-26, 2005.
16. Hamioud, F., Joannis, C., Ragot, J. (2005b). Localisation de défauts de capteur pour la validation des mesures hydrométriques issues de réseaux d'assainissement. 20ème colloque sur le traitement du signal et de l'image GRETSI 2005-Louvain la Neuve Belgique, 6-9 septembre 2005.
17. Harkat M.F., Mourot G., Ragot J. An improved PCA scheme for sensor FDI: Application to an air quality monitoring network. Journal of Process Control July 2006, 16(6):625-634.
18. Jörgensen H.K, Rosenörn S., Madsen H., Mikkelsen P.S. Quality control of rain data used for urban run-off systems. Water Science and Technology 1998, 37(11):113-120.
19. Kempowsky, T., Aguilar-Martin, J., Subias, A., Le Lann, M. V. (2003). Classification tool based on interactivity between expertise and self-learning techniques. In Proceedings of IFAC Safeprocess 2003, Washington DC, USA, 2003.
20. Kempowsky, T. (2004). Surveillance de procédés à base de methods de classification: Conception d'un outil d'aide pour la detection et le diagnostic des défaillances. Doctoral Thesis, Institut National des Sciences Appliquées de Toulouse, France.
21. Kempowsky T., Subias A., Aguilar-Martin J. Process situation assessment: From a fuzzy partition to a finite state machine. Engineering Applications of Artificial Intelligence 2006, 19(5):461-477.
22. Lobanova, H. V., Lobanova, G. V. (2003). Approach for restoration of missing data, long-term time series and generalization of results. In C. Maksimovic, D. Butler, & F. A. Memon (Eds.), Advances in water supply management. The Netherlands: Swets & Zeitlinger Publishers.
23. Maul-Kötter B., Einfalt T. Correction and preparation of continuously measured rain gauge data: A standard method in North Rhine-Westphalia. Water Science and Technology 1998, 37(11):155-162.
24. Maidment D.R., Parzen E. Time patterns of water uses in six Texas cities. Journal of Water Resources Planning and Management, ACSE 1984, 110(1):90-106.
25. Maidment D.R., Parzen E. Cascade model of monthly municipal water use. Water Resources Research 1984, 20(1):15-23.
26. Maidment D.R., Miaou S.P., Crawford M.M. Transfer function models of daily urban water use. Water Resources Research 1985, 21(4):425-432.
27. Matheson, D., Jing, C., Monforte, F. (2004). Meter data management for the electricity market. In Proceedings of the eighth international conference on probabilistic methods applied to power systems, Iowa State University, Ames, Iowa, September.
28. Miaou S.P. A class of time series urban water demand models with non-linear climatic effects. Water Resources Research 1990, 26(2):169-178.
29. Mourad M., Bertrand-Krajeswski J.L. A method for automatic validation of long time series of data in urban hydrology. Water Science and Technology 2002, 45(4-5):263-270.
30. Nelson P., Taylor P., MacGregor J. Missing data methods in PCA and PLS: Score calculations with incomplete observations. Journal of Chemometrics and Intelligent Laboratory Systems 1996, 35:45-65.
31. Pastres R., Ciavatta S., Solidoro C. The Extended Kalman Filter (EKF) as a tool for the assimilation of high frequency water quality data. Ecological Modelling 2003, 170(2-3):227-235. 15.
32. Petit-Renaud, S., Denoeux, T. (1998). A neuro-fuzzy system for missing data reconstruction. In Proceedings of the IEEE workshop on emerging technologies, intelligent measurement and virtual systems for instrumentation and measurement, Saint-Paul, USA, May 1998.
33. Piatyszek E., Voignier P., Graillot D. Fault detection on a sewer network by a combination of a Kalman filter and a binary sequential probability ratio test. Journal of Hydrology 2000, 230(3-4):258-268.
34. Piera N., Aguilar-Martin J. Controlling selectivity in nonstandard pattern recognition algorithms. IEEE Transactions on Systems, Man, and Cybernetics 1991, January-February:71-81.
35. Prescott S.L., Ulanicki B. Time series analysis of leakage in water distribution networks in water software systems theory and applications 2001, Research Studies Press, England.
36. Puig V., Quevedo J., Figueras J., Riera S., Cembrano G., Salamero M., Wilhelmi G. Fault detection and isolation of rain gauges and limnimeters of Barcelona's sewer system using interval models 2003, IFAC SafeProcess, Washington, USA.
37. Quevedo J., Cembrano G., Valls A., Serra J. Time-series modelling of water demand-A study on short-term and long-term predictions in computer applications in water supply 1988, Research Studies Press, England. B. Coulbeck, C.H. Orr (Eds.).
38. Ragot J., Maquin D. Fault measurement detection in an urban water supply network. Journal of Process Control 2006, 16(9):887-902.
39. Shvartser L., Shamir U., Fedman M. Forecasting hourly water demands by pattern recognition approach. Journal of Water Resources Planning and Management, ASCE 1993, 119(6):51-64.
40. Smith, J. A. (1988). A model of daily municipal water use for short-term forecasting. Water Research Resources, 24(2), 201-206.
41. Tsang K.M. Sensor data validation using gray models. ISA Transactions 2003, 42:9-17.
42. Valentin N., Denoeux T. A neural network-based software sensor for coagulation control in a water treatment plant. Intelligent Data Analysis 2001, 5:23-39.
43. Zhou S.L., McMahon T.A., Walton A., Lewis J. Forecasting operational demand for an urban water supply zone. Journal of Hydrology 2002, 259:189-202.