Proceedings of International Conference on Computer Science and Communication Engineering (ICCSCE 2025)

Acoustic Based Leak Detection System

Authors
Saleh Hamed Alawi1, *, Mohsin Amirza1, S. Kannadhasan2
1Department of Electronics and Telecommunication Engineering, Global College of Engineering and Technology(GCET), P.O. Box 2546 CPO Ruwi 112, Muscat, Sultanate of Oman
2Department of Electronics and Communication Engineering, Study World College of Engineering, Coimbatore, Tamilnadu, India
*Corresponding author.
Corresponding Author
Saleh Hamed Alawi
Available Online 4 November 2025.
DOI
10.2991/978-94-6463-858-5_186How to use a DOI?
Keywords
Acoustic Leak Detection; Matched Field Processing; Pipeline Monitoring; Environmental Sustainability; Signal Processing
Abstract

The increasing frequency of pipeline breaches across sectors necessitates the development of more accurate and effective leak detection technologies. Because pipeline leaks have increased. The economy and ecology may suffer if traditional localization and identification techniques don’t work. By using Matched Field Processing (MFP) to enhance acoustic-based leak detection, this study tackles the problem. By improving the accuracy and dependability of pipeline leak detection and localization, the system accomplishes its objective. The goal of this research was to create a system that can precisely locate and measure leaks in practical situations. This was our primary goal. To achieve this, we used sophisticated signal processing and high-sensitivity sound sensors. Thus, we achieved our goal. We thoroughly examined the flexibility and effectiveness of these parts. These studies took ambient noise, fluid types, and pipe materials into account. According to experimental findings, the system can detect leaks with very minor localization problems. The conclusion was shown by the trial outcomes. Proper specification of leak sizes and the ability to locate leaks within four meters made concentrated and efficient maintenance feasible. We completed everything. Across many test sets, the technology demonstrated sensitivity and dependability. This data demonstrates that the method is effective in industrial environments. Issues such as separating ambient sounds from leaks were resolved by the system’s enhanced noise discrimination. The system’s enhanced capabilities made this possible. The upgrade was necessary to guarantee that the system operated well in noisy industrial environments, where previous systems had failed. The acoustic-based leak detection technique enhanced the technology for pipeline monitoring. According to rigorous testing, the system has the ability to alter pipeline maintenance. The accuracy, reliability, and effectiveness of the system demonstrate its potential in enhancing the sustainability and safety of industrial processes. More pipeline systems and operating conditions will be able to use the enhanced noise-cancelling technology.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of International Conference on Computer Science and Communication Engineering (ICCSCE 2025)
Series
Advances in Computer Science Research
Publication Date
4 November 2025
ISBN
978-94-6463-858-5
ISSN
2352-538X
DOI
10.2991/978-94-6463-858-5_186How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Saleh Hamed Alawi
AU  - Mohsin Amirza
AU  - S. Kannadhasan
PY  - 2025
DA  - 2025/11/04
TI  - Acoustic Based Leak Detection System
BT  - Proceedings of International Conference on Computer Science and Communication Engineering (ICCSCE 2025)
PB  - Atlantis Press
SP  - 2230
EP  - 2244
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-858-5_186
DO  - 10.2991/978-94-6463-858-5_186
ID  - Alawi2025
ER  -