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Noise source identification in indoor substation using a sparse equivalent source method
Author(s) -
Luwen Xu,
Bo Yang,
Haitao Wang,
Lin Zhang,
Yaocheng Nie
Publication year - 2021
Publication title -
iop conference series earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1315
pISSN - 1755-1307
DOI - 10.1088/1755-1315/647/1/012073
Subject(s) - reverberation , ambient noise level , acoustics , noise (video) , computer science , transfer function , transformer , sampling (signal processing) , background noise , sound pressure , electronic engineering , engineering , artificial intelligence , electrical engineering , sound (geography) , telecommunications , physics , image (mathematics) , detector , voltage
Noise source identification is a key step in the noise control design of the transformer. The sound propagation is influenced by the reverberation effect in the indoor substation, which leads that the traditional method cannot give correct results in such environment. To supress the reverberation effect, a sparse equivalent source method is proposed to realize the noise source identification in indoor substation. This method first establishes the indoor sound transfer function model between the equivalent source surface and the acquisition surface by using wave simulation. Based on the wave simulation and combined with the sound pressure sampling data, the distributed equivalent source is recovered on the equivalent source surface by sparse recovery algorithm, and finally the sound pressure reconstruction on the reconstruction surface is realized. The numerical verification demonstrates that this method is capable of extracting the real noise information in the reverberation sound and giving the real noise source distribution result. This method can be used as an effective method in the noise source identification in the indoor substation.

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