Evidence map›Paper›PMID 41597920›Full record

ArticleMicromachines2026

Design of MEMS Microphone Array Integrated System for Pipeline Leakage Detection.

Kaixuan Wang, Yong Yang, Daoguang Liu, Di Song, Xiaoli Zhao

Abstract read
In one paragraph

Article in Micromachines, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Kaixuan WangSchool of Information Engineering, Xuzhou College of Industrial Technology, Xuzhou 221140, China.ORCID 0009-0000-2723-6484
Yong YangSchool of Information Engineering, Xuzhou College of Industrial Technology, Xuzhou 221140, China.
Daoguang LiuSchool of Information Engineering, Xuzhou College of Industrial Technology, Xuzhou 221140, China.
Di SongSchool of Civil Engineering, Southeast University, Nanjing 211189, China.ORCID 0000-0003-2728-3672
Xiaoli ZhaoSchool of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China.

Funding

Jiangsu Funding Program for Excellent Postdoctoral Talent 2025ZB343National Natural Science Foundation of China 52205062Natural Science Foundation of Jiangsu Province BK20220950Research Project of Xuzhou College of Industrial Technology for Distinguished Young Scholars XGY2025ZXJQ03
6 · The paper itself

Abstract

Pressure pipelines are widely used in the energy and transportation fields for conveying natural gas, water, etc. Under complex and harsh conditions with long-term operation, this easily leads to leakage, threatening the safe and stable operation of transportation systems. Although acoustic sensors support non-destructive leakage detection, their accuracy is restricted by noise interference and minor leakage uncertainties, and existing systems lack a targeted integration design for pipeline scenarios. To address this, the micro-electromechanical system (MEMS) is specifically designed as an MEMS microphone array integrated system (MEMS-MAIS), which is applied for pipeline leakage detection through data fusion at different levels. First, a dedicated MEMS microphone array system is designed to realize high-sensitivity collection of leakage acoustic data. In addition, the integrated feature extraction and feature-level fusion modules are proposed to retain effective information, and a decision-level fusion module is incorporated to improve the reliability of leakage detection results. To verify the designed system, an experiential platform is established with several microphone data. The results indicate that the proposed MEMS-MAIS exhibits excellent anti-interference performance and leakage detection accuracy of 94.67%. It provides a reliable integrated system solution for pipeline leakage detection and verifying high engineering application value.

Indexed as

integrated systemleakage detectionmicro-electromechanical system (MEMS)microphones arraypipeline

Identifiers

PMID41597920
PMCPMC12844459

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.