Real-Time Remote Localization of Gas Pipe Leakage Using Acoustic Beamforming and Spatial Filtering—A Lightweight Approach

In-situ monitoring of pipe leak becomes a daunting task, even with state-of-art sensing methods, if the pipe happens to be in an inaccessible indoor location. While acoustic wideband beamforming method exists for the same, the dynamic noise and sensors' susceptibility to malfunction in an industrial environment needs to be addressed. This work presents a joint spectral focusing and fault tolerant paradigm with a novel sound source separation algorithm as a fallback leak diagnostics tool. Computation and communication costs are reduced by processing voluminous array sensor data at the edge, and transmitting the lightweight audio-visual information to the operator for remote localization and diagnostics. The localization accuracy for the proposed method has been found to be within 5% for different experimental conditions.

Authors

Publication Details

Journal
IEEE Sensors Letters
Published
2025-05-29
DOI
https://doi.org/10.1109/lsens.2025.3574858
Citations
2
Primary Topic
Water Systems and Optimization
Type
article
Field-Weighted Citation Impact
1.91
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article

Real-Time Remote Localization of Gas Pipe Leakage Using Acoustic Beamforming and Spatial Filtering—A Lightweight Approach

Chirabrata Bhaumik, Raj Rakshit, Amit Swain, Mayukh Biswas
2 citations
IEEE Sensors Letters
Water Systems and Optimization
1.91
article

Real-Time Remote Localization of Gas Pipe Leakage Using Acoustic Beamforming and Spatial Filtering—A Lightweight Approach

Chirabrata Bhaumik, Raj Rakshit, Amit Swain, Mayukh Biswas
article en
2 citations

Abstract

In-situ monitoring of pipe leak becomes a daunting task, even with state-of-art sensing methods, if the pipe happens to be in an inaccessible indoor location. While acoustic wideband beamforming method exists for the same, the dynamic noise and sensors' susceptibility to malfunction in an industrial environment needs to be addressed. This work presents a joint spectral focusing and fault tolerant paradigm with a novel sound source separation algorithm as a fallback leak diagnostics tool. Computation and communication costs are reduced by processing voluminous array sensor data at the edge, and transmitting the lightweight audio-visual information to the operator for remote localization and diagnostics. The localization accuracy for the proposed method has been found to be within 5% for different experimental conditions.

IEEE Sensors LettersVol. 9(7)
Affordable and clean energy
Openalex Percentile: Top 15%
Water Systems and Optimization
1.91
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