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一种基于分布式卡尔曼滤波器的分布式计算解决方案，用于基于无线传感器网络的输水管道监测中的泄漏检测。

A Distributed Computing Solution Based on Distributed Kalman Filter for Leak Detection in WSN-Based Water Pipeline Monitoring.

作者信息

Nkemeni Valery, Mieyeville Fabien, Tsafack Pierre

机构信息

Université Claude Bernard Lyon 1, Ampère-CNRS UMR5005, F-69621 Villeurbanne, France.

University of Buea, Faculty of Engineering and Technology, P.O. Box 63 Buea, Cameroon.

出版信息

Sensors (Basel). 2020 Sep 12;20(18):5204. doi: 10.3390/s20185204.

DOI:10.3390/s20185204
PMID:32932618
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7570586/
Abstract

Wireless Sensor Network (WSN) applications that favor more local computations and less communication can contribute to solving the problem of high power consumption and performance issues plaguing most centralized WSN applications. In this study, we present a fully distributed solution, where leaks are detected in a water distribution network via only local collaborations between a sensor node and its close neighbors, without the need for long-distance transmissions via several hops to a centralized fusion center. A complete approach that includes the design, simulation, and physical measurements, showing how distributed computing implemented via a distributed Kalman filter improves the accuracy of leak detection and the power consumption is presented. The results from the physical implementation show that distributed data fusion increases the accuracy of leak detection while preserving WSN lifetime.

摘要

倾向于更多本地计算和更少通信的无线传感器网络（WSN）应用，有助于解决困扰大多数集中式WSN应用的高功耗和性能问题。在本研究中，我们提出了一种完全分布式解决方案，其中仅通过传感器节点与其近邻之间的本地协作来检测配水管网中的泄漏，而无需通过多跳进行长距离传输到集中式融合中心。本文提出了一种完整的方法，包括设计、仿真和物理测量，展示了如何通过分布式卡尔曼滤波器实现的分布式计算提高泄漏检测的准确性和功耗。物理实现的结果表明，分布式数据融合在保持WSN寿命的同时提高了泄漏检测的准确性。

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