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Time and Energy Savings in Leak Detection in WSN-Based Water Pipelines: A Novel Parametric Optimization-Based Approach

  • Muhammad MysorewalaEmail author
Article
  • 27 Downloads

Abstract

This paper presents a novel optimization algorithm for monitoring a complex water pipeline using Wireless Sensor Networks (WSN), in order to solve the trade-off between a timely and accurate detection of a leak, and an efficient utilization of the energy at the WSN’s nodes aimed at prolonging the WSN’s lifetime. The scheme relies on using vibration sensors of different sensitivities to detect vibrations due to a leak, and on exploiting duty-cycling, hierarchical adaptive sampling and wavelet-based signal compression, in order to reduce sensing, computation and communication energies. Given the constraints of a maximum allowable sensor energy, a limited time to detect a leak after it occurs, and an acceptable percentage of signal distortion due to compression, a new optimization-based backtracking learning algorithm is developed here that solves for the values of various monitoring parameters such that it satisfies all the given constraints. Developing such an optimization algorithm has also required performing a sensitivity analysis, i.e. investigating the effect of changing the key monitoring parameters on the performance of leak detection and energy consumption. Simulation results for various cases successfully demonstrate the effectiveness of the algorithm while supporting the prediction of the sensitivity analysis.

Keywords

Adaptive sampling Energy efficiency Leak detection Optimization Vibration sensing Water pipeline Wavelet compression Wireless sensor network 

Notes

Acknowledgements

The author acknowledges the support provided by the Deanship of Scientific Research (DSR) at King Fahd University of Petroleum & Minerals (KFUPM) for funding this work through Project no. FT161017, and the numerous constructive discussions on this topic held with his team member Prof. L. Cheded.

Compliance with Ethical Standards

Conflict of Interest

There is no conflict of interest.

References

  1. Abbas M, AbuBaker K, Ayaz M, Mohamed H, Tariq M, Ahmed A, Faheem M (2018) Key Factors Involved in Pipeline Monitoring Techniques Using Robots and WSNs: Comprehensive Survey. Journal of Pipeline Systems Engineering and Practice 9(2):04018001CrossRefGoogle Scholar
  2. Anastasi G, Conti M, Di Francesco MD, Passarella A (2009) Energy conservation in wireless sensor networks: A survey. Ad Hoc Netw 7(3):537–568CrossRefGoogle Scholar
  3. Bhuiyan M, Wang G, Cao J, Wu J (2013) Energy and bandwidth-efficient Wireless Sensor Networks for monitoring high-frequency events. IEEE International Conference on Sensing, Communications and Networking, SECON 2013, pp. 194–202Google Scholar
  4. El-Darymli K, Khan F, Ahmed MH (2009) Reliability modeling of wireless sensor network for oil and gas pipelines monitoring. Sensors & Transducers 106(7):6–26Google Scholar
  5. Eliades G, Kyriakou M, Vrachimis S, Polycarpou M (2017) EPANET-MATLAB Toolkit: An Open-Source Software for Interfacing EPANET with MATLAB. Proc. 14th International Conference on Computing and Control for the Water Industry (CCWI), The Netherlands, p. 8Google Scholar
  6. Evans R, Blotter J, Stephens A (2004) Flow Rate Measurements Using Flow-Induced Pipe Vibration. J Fluids Eng 126(2):280CrossRefGoogle Scholar
  7. Jawhar I, Mohamed N, Shuaib K (2007) A framework for pipeline infrastructure monitoring using wireless sensor network. Wireless Telecommunications Symposium (WTS), pp. 1–7Google Scholar
  8. Kurp T, Gao R, Sah S (2010) An adaptive sampling scheme for improved energy utilization in wireless sensor networks. IEEE Instrumentation and Measurement Technology Conference (I2MTC), pp. 93–98Google Scholar
  9. Latré B, Mil P, Moerman I, Dhoedt B, Demeester P, Dierdonck NV (2006) Throughput and Delay Analysis of Unslotted IEEE 802.15.4. Journal of Networks 1(1):20–28CrossRefGoogle Scholar
  10. Marmarokopos K, Doukakis D, Frantziskonis G, Avlonitis M (2018) Leak Detection in Plastic Water Supply Pipes with a High Signal-to-Noise Ratio Accelerometer. Measurement and Control 51(1–2):27–37CrossRefGoogle Scholar
  11. Martini A, Troncossi M, Rivola A (2013) Vibration Monitoring as a Tool for Leak Detection in Water Distribution Networks. Proc Surveillance 7:1–9Google Scholar
  12. Molina-Espinosa L, Verde-Rodarte C, Cazarez-Candia O (2012) Mathematical model for pipeline leak simulation. Experimental and Theoretical Advances in Fluid Dynamics, Springer, pp. 303–311Google Scholar
  13. Qu Z, Feng H, Zeng Z, Zhuge J, Jin S (2010) A SVM-based pipeline leakage detection and pre-warning system. Measurement 43(4):513–519CrossRefGoogle Scholar
  14. Raghunathan V, Schurgers C, Park S, Srivastava M (2002) Energy-aware wireless microsensor networks. IEEE Signal Process Mag 19(2):40–50CrossRefGoogle Scholar
  15. Saqib N, Mysorewala M, Cheded L (2017a) A Multiscale Approach to Leak Detection and Localization in Water Pipeline Network. Water Resour Manag 31(12):3829–3842CrossRefGoogle Scholar
  16. Saqib N, Mysorewala M, Cheded L (2017b) A novel multi-scale adaptive sampling-based approach for energy saving in leak detection for WSN-based water pipelines. Meas Sci Technol 28(12):125102CrossRefGoogle Scholar
  17. Sayood K (2012) Introduction to data compression. NewnesGoogle Scholar
  18. Shinozuka M, Chou PH, Kim S, Kim HR, Yoon E, Mustafa H, Karmakar D (2010) Nondestructive Monitoring of a Pipe Network using a MEMS-Based Wireless Network. Proc. SPIE 7649, Nondestructive Characterization for Composite Materials, 76490PGoogle Scholar
  19. Stoianov I, Nachman L, Madden S, Tokmouline T, Csail M (2007) PIPENET: A Wireless Sensor Network for Pipeline Monitoring. 6th International Symposium on Information Processing in Sensor Networks, pp. 264–273Google Scholar
  20. Yazdekhasti S, Piratla K, Atamturktur S, Khan A (2017) Experimental evaluation of a vibration-based leak detection technique for water pipelines. Struct Infrastruct Eng 14(1):46–55CrossRefGoogle Scholar
  21. Zhou H, Luo D, Gao Y, Zuo D (2011) Modeling of Node Energy Consumption for Wireless Sensor Networks. Wirel Sens Netw 03(01):18–23CrossRefGoogle Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Systems Engineering DepartmentKing Fahd University of Petroleum and Minerals (KFUPM)DhahranSaudi Arabia

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