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A Novel Underdetermined Blind Source Separation Method and Its Application to Source Contribution Quantitative Estimation
- Source :
- Sensors, Vol 19, Iss 6, p 1413 (2019), Sensors (Basel, Switzerland), Sensors, Volume 19, Issue 6
- Publication Year :
- 2019
- Publisher :
- MDPI AG, 2019.
-
Abstract
- To identify the major vibration and radiation noise, a source contribution quantitative estimation method is proposed based on underdetermined blind source separation. First, the single source points (SSPs) are identified by directly searching the identical normalized time-frequency vectors of mixed signals, which can improve the efficiency and accuracy in identifying SSPs. Then, the mixing matrix is obtained by hierarchical clustering, and source signals can also be recovered by the least square method. Second, the optimal combination coefficients between source signals and mixed signals can be calculated based on minimum redundant error energy. Therefore, mixed signals can be optimally linearly combined by source signals via the coefficients. Third, the energy elimination method is used to quantitatively estimate source contributions. Finally, the effectiveness of the proposed method is verified via numerical case studies and experiments with a cylindrical structure, and the results show that source signals can be effectively recovered, and source contributions can be quantitatively estimated by the proposed method.
- Subjects :
- 0209 industrial biotechnology
Computer science
02 engineering and technology
Radiation
lcsh:Chemical technology
Biochemistry
Article
Analytical Chemistry
Matrix (mathematics)
020901 industrial engineering & automation
0202 electrical engineering, electronic engineering, information engineering
lcsh:TP1-1185
mixing matrix estimation
Electrical and Electronic Engineering
Instrumentation
Mixing (physics)
Computer Science::Databases
source contribution estimation
Noise (signal processing)
underdetermined blind source separation
020206 networking & telecommunications
Underdetermined blind source separation
Atomic and Molecular Physics, and Optics
Hierarchical clustering
Vibration
single source point
Algorithm
Energy (signal processing)
Subjects
Details
- Language :
- English
- ISSN :
- 14248220
- Volume :
- 19
- Issue :
- 6
- Database :
- OpenAIRE
- Journal :
- Sensors
- Accession number :
- edsair.doi.dedup.....396c0d0f304e7e549d050dbf5e87ae25