微电子机械系统
材料科学
压力传感器
传感器
声学
泄漏(经济)
电容感应
水听器
灵敏度(控制系统)
压电
作者
Wee Kee Phua,Sarbudeen Mohamed Rabeek,Beibei Han,Edwin Njihof,Tyler Tianlu Huang,Kevin T. C. Chai,Jason Hock Huat Yeo,Soon Thor Lim
出处
期刊:Water
[MDPI AG]
日期:2020-10-22
卷期号:12 (11): 2966-
被引量:1
摘要
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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