- freely available
Appl. Sci. 2019, 9(17), 3561; https://doi.org/10.3390/app9173561
2.1. BSS Model
- Mixing matrix, A, is a column full-rank matrix.
- The source signals are the zero-mean random signals that are not correlated in the time-space domain and correlated in the time domain.
- The source signal and noise are independent.
- The number of source signals is less than or equal to the number of the original signals.
2.2. Improved SOBI
2.3. Accuracy Assessment
3. Simulated Experiment and Analysis
4. On-Site Experiment and Analysis
4.1. Site Description and Data Acquisition
4.2. Results Analysis and Discussion
- A simulation experiment was performed to validate the feasibility of the improved SOBI signal de-noising method where three mixed signals were linearly mixed using three sets of simulation source signals with different frequency scales. The obtained correlation coefficients between each simulated source signal and the corresponding separated signal component were all greater than 0.99. The results showed that the improved SOBI signal de-noising method effectively distinguished the useful signals and noise signals from the mixed signals, which can be useful for signal de-noising of time-series displacements obtained using GBSAR.
- By fully considering the characteristics of the high-distance resolution GBSAR technique, the obtained dynamic time-series displacements of three adjacent monitoring points in the same time domain were selected as input signals. This was done in order to obtain the de-noised time-series displacement of the middle point among three adjacent monitoring points by using the improved SOBI signal de-noising method. Using a spectrum analysis, the separated noise components were effectively determined from the separated signals, and the original amplitude of the de-noised signal was recovered using an inverse reconstruction with a mixing matrix. The results showed that the improved SOBI signal de-noising method not only reduced the noise caused by the surrounding environment, but also reduced the noise caused by vibrations of the monitoring instrument.
- Compared with the EDM and EEMD signal de-noising methods, the improved SOBI signal de-noising method displayed a greater improvement in the indexes of NRR, NM, and SER for the obtained time-series displacement of a bridge using GBSAR. The results indicate that the improved SOBI signal de-noising method has a powerful signal de-noising ability.
Conflicts of Interest
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|Signal Components||Correlation Coefficients|
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