Cargando…
A High Sensitivity AlN-Based MEMS Hydrophone for Pipeline Leak Monitoring
In this work, a miniaturized, low-cost, low-power and high-sensitivity AlN-based micro-electro-mechanical system (MEMS) hydrophone is proposed for monitoring water pipeline leaks. The proposed MEMS Hydrophone consists of a piezoelectric micromachined ultrasonic transducer (PMUT) array, an acoustic m...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10057001/ https://www.ncbi.nlm.nih.gov/pubmed/36985061 http://dx.doi.org/10.3390/mi14030654 |
_version_ | 1785016258364702720 |
---|---|
author | Zhi, Baoyu Wu, Zhipeng Chen, Caihui Chen, Minkan Ding, Xiaoxia Lou, Liang |
author_facet | Zhi, Baoyu Wu, Zhipeng Chen, Caihui Chen, Minkan Ding, Xiaoxia Lou, Liang |
author_sort | Zhi, Baoyu |
collection | PubMed |
description | In this work, a miniaturized, low-cost, low-power and high-sensitivity AlN-based micro-electro-mechanical system (MEMS) hydrophone is proposed for monitoring water pipeline leaks. The proposed MEMS Hydrophone consists of a piezoelectric micromachined ultrasonic transducer (PMUT) array, an acoustic matching layer and a pre-amplifier amplifier circuit. The array has 4 (2 × 2) PMUT elements with a first-order resonant frequency of 41.58 kHz. Due to impedance matching of the acoustic matching layer and the 40 dB gain of the pre-amplifier amplifier circuit, the packaged MEMS Hydrophone has a high sound pressure sensitivity of −170 ± 2 dB (re: 1 V/μPa). The performance with respect to detecting pipeline leaks and locating leak points is demonstrated on a 31 m stainless leaking pipeline platform. The standard deviation (STD) of the hydroacoustic signal and Monitoring Index Efficiency (MIE) are extracted as features of the pipeline leak. A random forest model is trained for accurately classifying the leak and no-leak cases using the above features, and the accuracy of the model is about 97.69%. The cross-correlation method is used to locate the leak point, and the localization relative error is about 10.84% for a small leak of 12 L/min. |
format | Online Article Text |
id | pubmed-10057001 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-100570012023-03-30 A High Sensitivity AlN-Based MEMS Hydrophone for Pipeline Leak Monitoring Zhi, Baoyu Wu, Zhipeng Chen, Caihui Chen, Minkan Ding, Xiaoxia Lou, Liang Micromachines (Basel) Communication In this work, a miniaturized, low-cost, low-power and high-sensitivity AlN-based micro-electro-mechanical system (MEMS) hydrophone is proposed for monitoring water pipeline leaks. The proposed MEMS Hydrophone consists of a piezoelectric micromachined ultrasonic transducer (PMUT) array, an acoustic matching layer and a pre-amplifier amplifier circuit. The array has 4 (2 × 2) PMUT elements with a first-order resonant frequency of 41.58 kHz. Due to impedance matching of the acoustic matching layer and the 40 dB gain of the pre-amplifier amplifier circuit, the packaged MEMS Hydrophone has a high sound pressure sensitivity of −170 ± 2 dB (re: 1 V/μPa). The performance with respect to detecting pipeline leaks and locating leak points is demonstrated on a 31 m stainless leaking pipeline platform. The standard deviation (STD) of the hydroacoustic signal and Monitoring Index Efficiency (MIE) are extracted as features of the pipeline leak. A random forest model is trained for accurately classifying the leak and no-leak cases using the above features, and the accuracy of the model is about 97.69%. The cross-correlation method is used to locate the leak point, and the localization relative error is about 10.84% for a small leak of 12 L/min. MDPI 2023-03-14 /pmc/articles/PMC10057001/ /pubmed/36985061 http://dx.doi.org/10.3390/mi14030654 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Communication Zhi, Baoyu Wu, Zhipeng Chen, Caihui Chen, Minkan Ding, Xiaoxia Lou, Liang A High Sensitivity AlN-Based MEMS Hydrophone for Pipeline Leak Monitoring |
title | A High Sensitivity AlN-Based MEMS Hydrophone for Pipeline Leak Monitoring |
title_full | A High Sensitivity AlN-Based MEMS Hydrophone for Pipeline Leak Monitoring |
title_fullStr | A High Sensitivity AlN-Based MEMS Hydrophone for Pipeline Leak Monitoring |
title_full_unstemmed | A High Sensitivity AlN-Based MEMS Hydrophone for Pipeline Leak Monitoring |
title_short | A High Sensitivity AlN-Based MEMS Hydrophone for Pipeline Leak Monitoring |
title_sort | high sensitivity aln-based mems hydrophone for pipeline leak monitoring |
topic | Communication |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10057001/ https://www.ncbi.nlm.nih.gov/pubmed/36985061 http://dx.doi.org/10.3390/mi14030654 |
work_keys_str_mv | AT zhibaoyu ahighsensitivityalnbasedmemshydrophoneforpipelineleakmonitoring AT wuzhipeng ahighsensitivityalnbasedmemshydrophoneforpipelineleakmonitoring AT chencaihui ahighsensitivityalnbasedmemshydrophoneforpipelineleakmonitoring AT chenminkan ahighsensitivityalnbasedmemshydrophoneforpipelineleakmonitoring AT dingxiaoxia ahighsensitivityalnbasedmemshydrophoneforpipelineleakmonitoring AT louliang ahighsensitivityalnbasedmemshydrophoneforpipelineleakmonitoring AT zhibaoyu highsensitivityalnbasedmemshydrophoneforpipelineleakmonitoring AT wuzhipeng highsensitivityalnbasedmemshydrophoneforpipelineleakmonitoring AT chencaihui highsensitivityalnbasedmemshydrophoneforpipelineleakmonitoring AT chenminkan highsensitivityalnbasedmemshydrophoneforpipelineleakmonitoring AT dingxiaoxia highsensitivityalnbasedmemshydrophoneforpipelineleakmonitoring AT louliang highsensitivityalnbasedmemshydrophoneforpipelineleakmonitoring |