用升降式振动声传感器检测郊区配水干线漏水

IF 1.9 Q3 ENGINEERING, MECHANICAL
Vibration Pub Date : 2022-06-16 DOI:10.3390/vibration5020021
Lili Bykerk, Jaime Valls Miro
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引用次数: 3

摘要

供水管网(wdn)泄漏占全球公用事业非收入水(NRW)的很大比例。通常情况下,只有当水浮出水面时才会确认泄漏,从而可以追踪泄漏;然而,很大比例的泄漏可能永远不会浮出水面,导致大量的水损失和公用事业成本。主动泄漏检测(ALD)方法可用于检测隐藏的泄漏;然而,这些方法的成功很大程度上取决于可用的检测仪器和操作人员的经验。为了帮助检测隐藏的泄漏和表面泄漏,水公司越来越多地探索部署振动声传感器,用于临时结构健康监测。在本文中,从悉尼郊区部署的一系列临时Lift和Shift (L&S)振动声传感器中收集和整理了数据。生成时频和频域特征,以评估两种最先进的水泄漏检测二元分类模型的性能和适用性。从广泛的现场数据集得出的结果显示,提供可靠的泄漏检测结果,准确率至少为97%,假阳性率低。通过使用这种可靠的泄漏检测系统,公用事业公司可以简化泄漏检测和维修流程,有效地减轻NRW并减少客户中断。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Detection of Water Leaks in Suburban Distribution Mains with Lift and Shift Vibro-Acoustic Sensors
Leaks in Water Distribution Networks (WDNs) account for a large proportion of Non-Revenue Water (NRW) for utilities worldwide. Typically, a leak is only confirmed once water surfaces, allowing the leak to be traced; however, a high percentage of leaks may never surface, incurring large water losses and costs for utilities. Active Leak Detection (ALD) methods can be used to detect hidden leaks; however, the success of such methods is highly dependent on the available detection instrumentation and the experience of the operator. To aid in the detection of both hidden and surfacing leaks, deployment of vibro-acoustic sensors is being increasingly explored by water utilities for temporary structural health monitoring. In this paper, data were collected and curated from a range of temporary Lift and Shift (L&S) vibro-acoustic sensor deployments across suburban Sydney. Time-frequency and frequency-domain features were generated to assess the performance and suitability of two state-of-the-art binary classification models for water leak detection. The results drawn from the extensive field data sets are shown to provide reliable leak detection outcomes, with accuracies of at least 97% and low false positive rates. Through the use of such a reliable leak detection system, utilities can streamline their leak detection and repair processes, effectively mitigating NRW and reducing customer disruptions.
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来源期刊
CiteScore
3.20
自引率
0.00%
发文量
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审稿时长
10 weeks
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