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基于模型的 TDR 反演技术实现供水管漏点的精确检测与定位。

Accurate Detection and Localization of Water Pipe Leaks through Model-Based TDR Inversion.

机构信息

Department of Electrical and Information Engineering, Polytechnic University of Bari, Via E. Orabona 4, 70125 Bari, Italy.

Department of Engineering for Innovation, Complesso Ecotekne-Corpo O, University of Salento, 73100 Lecce, Italy.

出版信息

Sensors (Basel). 2023 Jan 8;23(2):710. doi: 10.3390/s23020710.

DOI:10.3390/s23020710
PMID:36679507
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9861414/
Abstract

The problem of water scarcity affects many areas of the world due to water mismanagement and overconsumption and, more recently, to climate change. Monitoring the integrity of distribution systems is, therefore, increasingly important to avoid the waste of clean water. This paper presents a new signal processing technique for enhancing the performance of the methodology of leak detection in water distribution pipes based on time domain reflectometry (TDR). The new technique is based on a particular kind of TDR inversion (spatial TDR) based on a "gray-box" lumped parameter model of the system. The model does not include, e.g., radiative phenomena, non-TEM (transverse electromagnetic) modes etc. but is capable of reproducing accurately the complicated reflectograms obtained by a TDR leak detection system assuming a proper profile of capacitance per unit length along the sensing element. Even more importantly, the model is identified using only the reflectograms taken by the system with very little prior information about the system components. The developed technique is able to estimate with good accuracy, from reflectograms with unclear or ambiguous interpretation, the position and the extension of a region where water is located. The measurement is obtained without prior electromagnetic characterization of the TDR system components and without the need of modeling or quantifying a number of electromagnetic effects typical of on-site measurements.

摘要

水资源短缺问题影响着世界上许多地区,这是由于水资源管理不善和过度消耗,以及最近由于气候变化造成的。因此,监测分配系统的完整性对于避免清洁水的浪费变得越来越重要。本文提出了一种新的信号处理技术,用于提高基于时域反射计(TDR)的水分配管道泄漏检测方法的性能。该新技术基于一种特殊类型的 TDR 反演(空间 TDR),基于系统的“灰箱”集总参数模型。该模型不包括例如辐射现象、非 TEM(横电磁)模式等,但能够准确地再现 TDR 泄漏检测系统获得的复杂反射图,前提是沿感应元件具有适当的单位长度电容分布。更重要的是,该模型仅使用系统拍摄的反射图进行识别,而无需有关系统组件的先验信息。所开发的技术能够从解释不清晰或模糊的反射图中,准确估计水所在区域的位置和延伸范围。该测量是在无需对 TDR 系统组件进行电磁特性预先表征的情况下,以及无需对现场测量中典型的许多电磁效应进行建模或量化的情况下完成的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df90/9861414/082ea3988a55/sensors-23-00710-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df90/9861414/1be1c7e68de1/sensors-23-00710-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df90/9861414/b22218348ccc/sensors-23-00710-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df90/9861414/632a9b6946ea/sensors-23-00710-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df90/9861414/47680404f709/sensors-23-00710-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df90/9861414/12713c02682e/sensors-23-00710-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df90/9861414/e8b75f7d809e/sensors-23-00710-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df90/9861414/a1b3b0aada25/sensors-23-00710-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df90/9861414/76d9a5d562c6/sensors-23-00710-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df90/9861414/b04ea18ce6da/sensors-23-00710-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df90/9861414/ce43d802075a/sensors-23-00710-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df90/9861414/f621bd814791/sensors-23-00710-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df90/9861414/082ea3988a55/sensors-23-00710-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df90/9861414/1be1c7e68de1/sensors-23-00710-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df90/9861414/b22218348ccc/sensors-23-00710-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df90/9861414/632a9b6946ea/sensors-23-00710-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df90/9861414/47680404f709/sensors-23-00710-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df90/9861414/12713c02682e/sensors-23-00710-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df90/9861414/e8b75f7d809e/sensors-23-00710-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df90/9861414/a1b3b0aada25/sensors-23-00710-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df90/9861414/76d9a5d562c6/sensors-23-00710-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df90/9861414/b04ea18ce6da/sensors-23-00710-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df90/9861414/ce43d802075a/sensors-23-00710-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df90/9861414/f621bd814791/sensors-23-00710-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df90/9861414/082ea3988a55/sensors-23-00710-g012.jpg

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