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Sound source identification algorithm for compressed beamforming

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Abstract

Microphone array-based beamforming algorithms are widely used in sound source identification, fault diagnosis, and radar communication because of their excellent performance. However, their limited spatial resolution and high dynamic side flap level seriously affect the recognition accuracy. To explore a high-performance beamforming sound source identification algorithm, the microphone array compressed beamforming underdetermined equation is solved by extending the iterative threshold. A sound source identification model is established, and a new compressed beamforming (CSB-II) algorithm is proposed. Numerical simulations show that the CSB-II algorithm can effectively reduce the starting frequency of sound source identification and has high sound source identification accuracy. The effects of signal-to-noise ratio, sound source distance, and array number on sound source identification accuracy are analyzed separately. The laws affecting sound source identification accuracy are derived from guiding actual sound source measurements.

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Acknowledgments

This work is supported by the National Natural Science Foundation of China (52075439), China, the Doctoral Dissertation Innovation Fund of Xi’an University of Technology (252072203), China, and Xi’an Science and Technology Plan Project (23GXFW0049), China.

Author information

Authors and Affiliations

  1. School of Mechanical and Precision Instrument Engineering, Xi’an University of Technology, Xi’an, 710048, P.R. China

    Jian Sun, Pengyang Li, Yunshuai Chen, Han Lu & Guoqing Chen

  2. Qinchuan Group (Xi’an) Technology Research Institute Co., Ltd., Xi’an, 710018, P.R. China

    Ding Shao

Authors
  1. Jian Sun
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  2. Pengyang Li
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  3. Yunshuai Chen
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  4. Han Lu
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  5. Ding Shao
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  6. Guoqing Chen
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Corresponding author

Correspondence to Pengyang Li.

Additional information

Jian Sun is currently a Ph.D. student at the School of Mechanical and Precision Instrument Engineering, Xi’an University of Technology, Shaanxi, China. His research interests are in ultrasonic vibration-assisted machining and sound source identification.

Pengyang Li is currently a Professor and doctoral supervisor of the School of Mechanical and Precision Instrument Engineering, Xi’an University of Technology, Shaanxi, China. His research direction is intelligent manufacturing technology and ultrasonic vibration assisted processing.

Yunshuai Chen is currently a Ph.D. student at the School of Mechanical and Precision Instrument Engineering, Xi’an University of Technology, Shaanxi, China. His research interests are in dynamic characteristics and stability control of ultrasonic machining system.

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Cite this article

Sun, J., Li, P., Chen, Y. et al. Sound source identification algorithm for compressed beamforming. J Mech Sci Technol 38, 1627–1634 (2024). https://doi.org/10.1007/s12206-024-0301-z

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  • DOI: https://doi.org/10.1007/s12206-024-0301-z

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