Distributed Compressed Sensing of Microseismic Signals Through First Break Time Extraction and Signal Alignment
Microseismic monitoring is widely applied in dams, mines, and various fields of underground engineering. The number of sensors in microseismic monitoring systems is usually very large, which will result in a huge amount of data being produced if the Nyquist sampling theorem is used to acquire micros...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2018-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8351901/ |
| _version_ | 1818557230971092992 |
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| author | Ran Zhang Qingsong Hu Gang Wang Bin Ye |
| author_facet | Ran Zhang Qingsong Hu Gang Wang Bin Ye |
| author_sort | Ran Zhang |
| collection | DOAJ |
| description | Microseismic monitoring is widely applied in dams, mines, and various fields of underground engineering. The number of sensors in microseismic monitoring systems is usually very large, which will result in a huge amount of data being produced if the Nyquist sampling theorem is used to acquire microseismic signals. To reduce the data storage costs and accelerate the transmission speed, we propose a distributed compressed sensing (CS) scheme for microseismic monitoring signals in this paper. The distributed compressed sensing scheme begins when it detects the first break time in the microseismic signal. The data recoding of the first break time is coded and transmitted together with the measured values of CS. Depending on the correlations between the microseismic signals, the first break time of the signals are aligned to that of the reference signal. Furthermore, we make use of the distributed CS to reduce the amount of data to be transmitted and to increase the reconstruction accuracy. Simulation results show that, compared with the sampling scheme based on the Nyquist sampling theorem, the independent CS scheme or the traditional distributed CS scheme, our proposed scheme improves the accuracy in the first break time detection and the reconstruction accuracy, and the scheme reduces the energy consumption at the same time. |
| first_indexed | 2024-12-13T23:57:07Z |
| format | Article |
| id | doaj.art-88ed4ca489054de1b15c5cdc161f6739 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-13T23:57:07Z |
| publishDate | 2018-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-88ed4ca489054de1b15c5cdc161f67392022-12-21T23:26:30ZengIEEEIEEE Access2169-35362018-01-016274082741710.1109/ACCESS.2018.28309748351901Distributed Compressed Sensing of Microseismic Signals Through First Break Time Extraction and Signal AlignmentRan Zhang0https://orcid.org/0000-0001-8628-3803Qingsong Hu1Gang Wang2Bin Ye3https://orcid.org/0000-0001-6697-1166School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, ChinaSchool of Information and Control Engineering, China University of Mining and Technology, Xuzhou, ChinaSchool of Information and Control Engineering, China University of Mining and Technology, Xuzhou, ChinaSchool of Information and Control Engineering, China University of Mining and Technology, Xuzhou, ChinaMicroseismic monitoring is widely applied in dams, mines, and various fields of underground engineering. The number of sensors in microseismic monitoring systems is usually very large, which will result in a huge amount of data being produced if the Nyquist sampling theorem is used to acquire microseismic signals. To reduce the data storage costs and accelerate the transmission speed, we propose a distributed compressed sensing (CS) scheme for microseismic monitoring signals in this paper. The distributed compressed sensing scheme begins when it detects the first break time in the microseismic signal. The data recoding of the first break time is coded and transmitted together with the measured values of CS. Depending on the correlations between the microseismic signals, the first break time of the signals are aligned to that of the reference signal. Furthermore, we make use of the distributed CS to reduce the amount of data to be transmitted and to increase the reconstruction accuracy. Simulation results show that, compared with the sampling scheme based on the Nyquist sampling theorem, the independent CS scheme or the traditional distributed CS scheme, our proposed scheme improves the accuracy in the first break time detection and the reconstruction accuracy, and the scheme reduces the energy consumption at the same time.https://ieeexplore.ieee.org/document/8351901/Compressed sensingfirst break timemicroseismic signalsignal samplingsignal reconstruction |
| spellingShingle | Ran Zhang Qingsong Hu Gang Wang Bin Ye Distributed Compressed Sensing of Microseismic Signals Through First Break Time Extraction and Signal Alignment IEEE Access Compressed sensing first break time microseismic signal signal sampling signal reconstruction |
| title | Distributed Compressed Sensing of Microseismic Signals Through First Break Time Extraction and Signal Alignment |
| title_full | Distributed Compressed Sensing of Microseismic Signals Through First Break Time Extraction and Signal Alignment |
| title_fullStr | Distributed Compressed Sensing of Microseismic Signals Through First Break Time Extraction and Signal Alignment |
| title_full_unstemmed | Distributed Compressed Sensing of Microseismic Signals Through First Break Time Extraction and Signal Alignment |
| title_short | Distributed Compressed Sensing of Microseismic Signals Through First Break Time Extraction and Signal Alignment |
| title_sort | distributed compressed sensing of microseismic signals through first break time extraction and signal alignment |
| topic | Compressed sensing first break time microseismic signal signal sampling signal reconstruction |
| url | https://ieeexplore.ieee.org/document/8351901/ |
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