Journal
MEASUREMENT SCIENCE AND TECHNOLOGY
Volume 31, Issue 9, Pages -Publisher
IOP Publishing Ltd
DOI: 10.1088/1361-6501/ab816f
Keywords
underdetermined convolutive blind source separation; mixing matrix estimation; single source points; source identification; contribution evaluation
Funding
- National Natural Science Foundation of China [51775407]
- National Key Research and Development Program of China [2019YFB1705403]
- General Project of Joint Pre-research Fund for Equipment of Ministry of Education [6141A02022121]
- Fundamental Research Funds for the Central Universities
- Innovative Scientific Program of CNNC
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To effectively separate underdetermined convolutive mixtures, an accurate and robust underdetermined convolutive blind source separation (BSS) method in the time-frequency domain based on single source points (SSPs) is proposed. Firstly, convolutive BSS in the time domain is transformed into instantaneous BSS in the time-frequency domain by short-time Fourier transform (STFT). Secondly, hierarchical clustering is carried out after the extraction and identification of SSPs by using sparse coding technology. Thirdly, source separation in the frequency domain is obtained based onL(p)norm minimization and then alignments are permutated and scales are compensated. Finally, inverse STFT is adopted to reconstruct the separated signals in the time domain. Furthermore, numerical case studies and experimental case studies on a cylindrical test bed are carried out to validate the effectiveness of the proposed method. Generally, this paper provides an accurate and robust underdetermined convolutive BSS technique for mixing matrix estimation, source identification and contribution evaluation, which can provide significant evidence for vibration and noise monitoring and control.
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