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首页> 外文期刊>Water Resources Management >Time and Energy Savings in Leak Detection in WSN-Based Water Pipelines: A Novel Parametric Optimization-Based Approach
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Time and Energy Savings in Leak Detection in WSN-Based Water Pipelines: A Novel Parametric Optimization-Based Approach

机译：基于WSN的输水管道泄漏检测中的时间和能源节省：一种基于参数优化的新方法

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摘要

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.
机译：本文提出了一种使用无线传感器网络（WSN）监控复杂水管道的新颖优化算法，以解决在及时准确地检测泄漏与有效利用WSN节点之间的权衡问题旨在延长WSN的寿命。该方案依赖于使用具有不同灵敏度的振动传感器来检测由于泄漏引起的振动，并利用占空比，分层自适应采样和基于小波的信号压缩来减少感测，计算和通信能量。考虑到最大允许传感器能量，泄漏发生后的有限时间以及压缩导致的信号失真的可接受百分比的限制，此处开发了一种新的基于优化的回溯学习算法，该算法可解决各种值监视参数，使其满足所有给定的约束。开发这种优化算法还需要执行灵敏度分析，即研究更改关键监控参数对泄漏检测和能耗的影响。各种情况下的仿真结果成功地证明了该算法的有效性，同时支持了灵敏度分析的预测。

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