Research on airspace filtering algorithm for trackside train bearings based on GSC-MVDR Article Swipe

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Ziyu Yuan , Fang Liu , Xuewen Bao , Guangwen Ren , Guo‐Qiang Zeng , Yongbin Liu ·

YOU? · · 2024 · Open Access · · DOI: https://doi.org/10.1088/1742-6596/2842/1/012090

Trackside Acoustic Detection Systems (TADS) employ microphone arrays installed on both sides of the railway tracks to collect sound signals emitted by wheelset bearings as trains pass by. These systems facilitate state monitoring and fault diagnosis through signal processing, offering capabilities such as non-contact measurement, low cost, and early warning of potential failures. However, the strong noise characteristics of trackside signals significantly impair diagnostic precision. To address this issue, this paper proposes a spatial filtering algorithm based on the Minimum Variance Distortion-less Response (MVDR) and the Generalized Sidelobe Canceller (GSC), achieving directional denoising. Additionally, the algorithm employs time-domain resampling techniques to correct the Doppler effect in signals.

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Computer science Aeronautics Algorithm Speech recognition Engineering

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Type: article
Language: en
Landing Page: http://doi.org/10.1088/1742-6596/2842/1/012090
OA Status: diamond
References: 4
Related Works: 10
OpenAlex ID: https://openalex.org/W4402746885

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DOI: https://doi.org/10.1088/1742-6596/2842/1/012090

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Title: Research on airspace filtering algorithm for trackside train bearings based on GSC-MVDR

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Type: article

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Language: en

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Publication year: 2024

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Publication date: 2024-09-01

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Authors: Ziyu Yuan, Fang Liu, Xuewen Bao, Guangwen Ren, Guo‐Qiang Zeng, Yongbin Liu

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Landing page: https://doi.org/10.1088/1742-6596/2842/1/012090

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OA status: diamond

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OA URL: https://doi.org/10.1088/1742-6596/2842/1/012090

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Concepts: Computer science, Aeronautics, Algorithm, Speech recognition, Engineering

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Cited by: 0

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References (count): 4

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