Cable External Breakage Source Localization Method Based on Improved Generalized Cross-Correlation Phase Transform with Multi-Sensor Fusion

In response to the need for cable outer sound source localization, this paper proposes a collaborative localization method based on an improved generalized cross-correlation phase transform (GCC-PHAT) and multi-sensor fusion. By constructing a secondary cross-shaped sensor array model, employing a phase transform weighting function to suppress environmental noise, and incorporating an adaptive environmental compensation algorithm to eliminate multipath effects, a set of spatial localization equations is established. Innovatively, a dynamic weighting factor linked to the startup threshold is introduced; the Levenberg–Marquardt optimization algorithm is then used to iteratively solve the nonlinear equations to achieve preliminary localization in a single-pile coordinate system. Finally, a dynamic weighted fusion model is constructed through DBSCAN spatial clustering to determine the final sound source position. Experimental results demonstrate that this method reduces the mean square error of time delay estimation by 94.7% in a 90 dB industrial noise environment, decreases the localization error by 65.4% in multi-obstacle scenarios, and ultimately maintains localization accuracy within 3 m over a range of 100 m. This performance is significantly superior to that of traditional TDOA and SRP-PHAT methods, offering a high-precision localization solution for underground cable protection.

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Publication Details

Journal
Energies
Published
2025-05-20
DOI
https://doi.org/10.3390/en18102628
Citations
1
Primary Topic
Speech and Audio Processing
Type
article
Field-Weighted Citation Impact
1.49

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article

Cable External Breakage Source Localization Method Based on Improved Generalized Cross-Correlation Phase Transform with Multi-Sensor Fusion

Xu‐Wen Wang, Jiang Li
1 citations
Energies
Speech and Audio Processing
1.49
article

Cable External Breakage Source Localization Method Based on Improved Generalized Cross-Correlation Phase Transform with Multi-Sensor Fusion

Xu‐Wen Wang, Jiang Li
article en
1 citations

Abstract

In response to the need for cable outer sound source localization, this paper proposes a collaborative localization method based on an improved generalized cross-correlation phase transform (GCC-PHAT) and multi-sensor fusion. By constructing a secondary cross-shaped sensor array model, employing a phase transform weighting function to suppress environmental noise, and incorporating an adaptive environmental compensation algorithm to eliminate multipath effects, a set of spatial localization equations is established. Innovatively, a dynamic weighting factor linked to the startup threshold is introduced; the Levenberg–Marquardt optimization algorithm is then used to iteratively solve the nonlinear equations to achieve preliminary localization in a single-pile coordinate system. Finally, a dynamic weighted fusion model is constructed through DBSCAN spatial clustering to determine the final sound source position. Experimental results demonstrate that this method reduces the mean square error of time delay estimation by 94.7% in a 90 dB industrial noise environment, decreases the localization error by 65.4% in multi-obstacle scenarios, and ultimately maintains localization accuracy within 3 m over a range of 100 m. This performance is significantly superior to that of traditional TDOA and SRP-PHAT methods, offering a high-precision localization solution for underground cable protection.

EnergiesVol. 18(10)
Shanghai University of Electric Power (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 19%
Speech and Audio Processing
1.49
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