New Failure Detection Approach for Real Time for Hydraulic Networks Using the Non-acoustic Method

  • Bala Moussa BiayeEmail author
  • Cherif Ahmed Tidiane Aidara
  • Amadou Coulibaly
  • Khalifa Gaye
  • Serigne Diagne
  • Edouard Ngor Sarr
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 111)


The management policy of infrastructures and equipments (e.g.: hydraulic, solar, sanitary, educational, etc.) disseminated throughout the country, particularly in rural areas, generally difficult to access, is a major challenge for the technical services of the State. The Infra-SEN intelligent Geographic Information System proposed in this paper aims to offer to organizations in charge of the management of infrastructures and equipments a platform that allows them to find out in real time how the equipments work and to detect any failures. In the present study, this paper is a contribution for analyzing the conditions of remote monitoring of hydraulic equipments. We use the failure mode, effects, and criticality analysis (FMECA) method in order to identify vulnerable equipments and analyze their Effects and their criticality. The solution proposed has been applied to the hydraulic installation at Niamone in the department of Bignona, in Ziguinchor region, in Senegal.


Database GIS Connected objects Measurements acquisition system 


  1. 1.
    Blindu, I.: Help tool for the diagnosis of the drinking water network for the city of Chisinau by spatial and temporal analysis of hydraulics dysfunctions. Ph.D., Jean Monnet University of Saint Etienne (2004)Google Scholar
  2. 2.
    Guépié, B.K.: Sequential detection of transient signals: application to the monitoring of a drinking water network. Ph.D., technology University of Troyes (2013)Google Scholar
  3. 3.
    Karima, S., Abdelhamid, S., Moula, Z.: Pre-localization approach of leaks on a water distribution network by optimization of the hydraulic model using an evolutionary algorithm. In: 2018 Proceedings of 3rd EWaS International Conference on “Insights on the Water-Energy-Food Nexus”, Lefkada Island, Greece, 27–30 June 2018, vol. 2, no. 11, p. 588 (2018)Google Scholar
  4. 4.
    Cheifetz, N., Sandraz, A.-C., Feliers, C., Gilbert, D., Piller, O., Heim, V.: A greedy algorithm for quality sensor placement on a large-scale water distribution network. In: TSM 2017, vol. 11, pp. 55–63 (2017)Google Scholar
  5. 5.
    Isenmann, G., Bellahcen, S., Vazquez, J., Dufresne, M., Joannis, C., Mose, R.: Evaluation of the discharge in an overflow pipe of a pumping station from the measurement of water depths. In: TSM 2016, 1–2, 71–83 (2016)Google Scholar
  6. 6.
    Butterfield, J.D., Meyers, G., Meruane, V., Collins, R.P., Beck, S.B.M.: Experimental investigation into techniques to predict leak shapes in water distribution systems using vibration measurements. J. Hydroinf. 20(4), 815–828 (2018)CrossRefGoogle Scholar
  7. 7.
    Aslam1, H., Kaur, M., Sasi, S., Mortula, Md.M., Yehia, S., Ali, T.: Detection of leaks in water distribution system using non-destructive techniques. In: 8th International Conference on Future Environment and Energy (ICFEE 2018). Earth and Environmental Science, vol. 150, p. 012004 (2018)CrossRefGoogle Scholar
  8. 8.
    Seyoum, S., Alfonso, L., van Andela, S.J., Koole, W., Groenewegen, A., van de Giesen, N.: A Shazam-like household water leakage detection method. Procedia Eng. 186, 452–459 (2017)CrossRefGoogle Scholar
  9. 9.
    Butterfield, J.D., Krynkin, A., Collins, R.P., Beck, S.B.M.: Experimental investigation into vibro-acoustic emission signal processing techniques to quantify leak flow rate in plastic water distribution pipes. Appl. Acoust. 119, 146–155 (2017)CrossRefGoogle Scholar
  10. 10.
    Dary, P.: Remote monitoring in heart failure: Feasibility and results of a limited 14-day follow-up of 83 patients. Eur. Res. Telemed. 3, 125–132 (2014)CrossRefGoogle Scholar
  11. 11.
    Hunaidi, O.: Leaks detection in water pipes, constructive solution no. 40. Institute for Research on Construction, Canadian National Research Council, 6 p. (2000)Google Scholar
  12. 12.
    Bentoumi, M., Chikouche, D., Bouamar, M., Khelfa, A.: implementation for real time a leak water detection algorithm distribution networks on the TMS320C6201 processor using acoustic correlation. In: 4th International Conference on Computer Integrated Manufacturing, CIP 2007, 03–04 November 2007 (2007)Google Scholar
  13. 13.
    (NDDWS, 2013) National Directorate of Drinking Water and Sanitation of Haiti loss control of water - search for leaks, Version 23, Septembre 2013Google Scholar
  14. 14.
    Almeida, F.C.L., Brennan, M.J., Joseph, P.F., Gao, Y., Paschoalini, A.T.: The effects of resonances on time delay estimation for water leak detection in plastic pipes. J. Sound Vibr. 420, 315–329 (2018)CrossRefGoogle Scholar
  15. 15.
    Gao, Y., Brennan, M.J., Liu, Y., Almeida, F.C.L., Joseph, P.F.: Improving the shape of the cross-correlation function for leak detection in a plastic water distribution pipe using acoustic signals. Appl. Acoust. 127, 24–33 (2017)CrossRefGoogle Scholar
  16. 16.
    Hunaidi, O. : Acoustic strategy of leaks on water distribution pipes, constructive solution n° 79. In: Canadian Institute for Research on Construction, Canadian National Research Council (2012)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Bala Moussa Biaye
    • 1
    Email author
  • Cherif Ahmed Tidiane Aidara
    • 1
  • Amadou Coulibaly
    • 1
    • 2
  • Khalifa Gaye
    • 1
    • 2
  • Serigne Diagne
    • 1
    • 2
  • Edouard Ngor Sarr
    • 3
  1. 1.Laboratory of Computer Science and Engineering for Innovation (LI3)Assane Seck University of ZiguinchorDiabirSenegal
  2. 2.Laboratory of Sciences of the Engineer, Computer Science and Imaging (Icube – UMR 7357), National Institute of Applied Sciences of StrasbourgUniversity of Strasbourg, CNRSStrasbourgFrance
  3. 3.Laboratory TIC-SI UCAO-SIDakar-Senegal University of ThiesThiesSenegal

Personalised recommendations