基于AIN的MEMS(微机电系统)水听器传感器用于物联网漏水检测系统

W. K. Phua, S. Rabeek, B. Han, Edwin Njihof, Tyler Tianlu Huang, K. Chai, J. Yeo, S. Lim
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引用次数: 10

摘要

工业物联网(IoT)解决方案迫切需要部署智能水听器传感器网格来监测管道健康状况,并在发生泄漏时提供准确的预测。一种解决方案是开发一种物联网漏水检测系统,该系统由一个接口组成,用于捕获来自基于氮化铝(AlN)的微机械次声水听器传感器的声音信号,该传感器作为输入输入,并预测泄漏的大致位置作为输出形式。微机电系统(MEMS)对于低功耗和小设备占用空间的物联网应用特别有用。数据分析包括特征、预处理/后处理,用于确定泄漏。在这项工作中,我们开发了检测管道泄漏的流程和算法,以准确地确定管道泄漏的位置。我们的方法可以用于检测不同管道长度、直径和材料的泄漏。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
AIN based MEMS (Micro-Electro-Mechanical System) Hydrophone Sensors for IoT Water Leakage Detection System
There is an urgent need for industrial Internet of things (IoT) solutions to deploy a smart hydrophone sensor grid to monitor pipeline health and to provide an accurate prediction in the event of any leakage. One solution is to develop an IoT water leakage detection system consisting of an interface to capture acoustic signals from aluminum nitride (AlN)-based micro-machined infrasonic hydrophone sensors that are fed as inputs and predict an approximate leak location as a form of output. Micro-electro-mechanical systems (MEMS) are particularly useful for IoT applications with low power consumption and small device footprint. Data analytics including characterization, pre/post processing are applied to determine the leaks. In this work, we have developed the process flow and algorithm to detect pipe leakage occurrence and pinpoint the location accurately. Our approach can be implemented to detect leaks for different pipe lengths, diameters and materials.
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