| Autor: |
Baofeng Tian, Chao Sun, Longchang Liu, Yue-Der Lin, Chuang-Chien Chiu, Haoyu Duan, Hui Luan |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
Frontiers in Earth Science, Vol 11 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2296-6463 |
| DOI: |
10.3389/feart.2023.1088290 |
| Popis: |
Magnetic resonance sounding (MRS) is a geophysical method that can determine groundwater content directly and quantitatively. However, as MRS uses the Earth’s magnetic field as the background field, MRS signals are weak and cannot be shielded. Reliably extracting MRS signals in a strong noise environment is difficult. In this study, a data processing scheme using the adaptive local iterative filtering (ALIF) algorithm is proposed to extract MRS signal envelopes accurately. Based on the uncertainty of the initial amplitude and relaxation time, the decomposition order and mask coefficient of the ALIF algorithm are selected via traversal. Simulation results show that in the case of Gaussian noise and power frequency harmonic noise, the ALIF algorithm can reliably extract the MRS signal envelopes, and the correlation coefficient between the extracted and noiseless envelopes is 0.97. Under various noise types, amplitudes, and relaxation times, the average SNR increases by 30 dB∼42 dB. The ALIF algorithm is also suitable for extracting multi-exponential MRS signal envelopes. A comparative analysis between harmonic modeling cancellation and ensemble empirical mode decomposition shows the superiority of the ALIF algorithm, and the processing of the field data further verifies the effectiveness and practicability of the algorithm. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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