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| Title: | A De-Noising Algorithm Based on EEMD in Raman-Based Distributed Temperature Sensor |
| Authors: | Liang Pan;Kun Liu;Junfeng Jiang;Chunyu Ma;Miao Tian;Tiegen Liu |
| Year: | 2017 |
| Publisher: | IEEE |
| Abstract: | A de-noising algorithm based on ensemble empirical mode decomposition (EEMD) method is employed in this paper for Raman-based distributed temperature sensor (RDTS). We first decompose the noisy signal using the EEMD and find local maxima on each intrinsic mode function (IMF) whose zero contour line is used to determine noise interval. The signal is then de-noised and reconstructed by removing the noise components of each IMF. The experimental results demonstrated that the proposed de-noising algorithm can enhance the signal-to-noise ratio by 8.8 dB while maintaining spatial resolution. The temperature error reduction of 3.2 &x00B0;C can be achieved at 10 km using conventional RDTS without losing any detail. |
| URI: | http://localhost/handle/Hannan/232658 |
| volume: | 17 |
| issue: | 1 |
| More Information: | 134, 138 |
| Appears in Collections: | 2017 |
Files in This Item:
| File | Size | Format | |
|---|---|---|---|
| 7728000.pdf | 1.07 MB | Adobe PDF |
| Title: | A De-Noising Algorithm Based on EEMD in Raman-Based Distributed Temperature Sensor |
| Authors: | Liang Pan;Kun Liu;Junfeng Jiang;Chunyu Ma;Miao Tian;Tiegen Liu |
| Year: | 2017 |
| Publisher: | IEEE |
| Abstract: | A de-noising algorithm based on ensemble empirical mode decomposition (EEMD) method is employed in this paper for Raman-based distributed temperature sensor (RDTS). We first decompose the noisy signal using the EEMD and find local maxima on each intrinsic mode function (IMF) whose zero contour line is used to determine noise interval. The signal is then de-noised and reconstructed by removing the noise components of each IMF. The experimental results demonstrated that the proposed de-noising algorithm can enhance the signal-to-noise ratio by 8.8 dB while maintaining spatial resolution. The temperature error reduction of 3.2 &x00B0;C can be achieved at 10 km using conventional RDTS without losing any detail. |
| URI: | http://localhost/handle/Hannan/232658 |
| volume: | 17 |
| issue: | 1 |
| More Information: | 134, 138 |
| Appears in Collections: | 2017 |
Files in This Item:
| File | Size | Format | |
|---|---|---|---|
| 7728000.pdf | 1.07 MB | Adobe PDF |
| Title: | A De-Noising Algorithm Based on EEMD in Raman-Based Distributed Temperature Sensor |
| Authors: | Liang Pan;Kun Liu;Junfeng Jiang;Chunyu Ma;Miao Tian;Tiegen Liu |
| Year: | 2017 |
| Publisher: | IEEE |
| Abstract: | A de-noising algorithm based on ensemble empirical mode decomposition (EEMD) method is employed in this paper for Raman-based distributed temperature sensor (RDTS). We first decompose the noisy signal using the EEMD and find local maxima on each intrinsic mode function (IMF) whose zero contour line is used to determine noise interval. The signal is then de-noised and reconstructed by removing the noise components of each IMF. The experimental results demonstrated that the proposed de-noising algorithm can enhance the signal-to-noise ratio by 8.8 dB while maintaining spatial resolution. The temperature error reduction of 3.2 &x00B0;C can be achieved at 10 km using conventional RDTS without losing any detail. |
| URI: | http://localhost/handle/Hannan/232658 |
| volume: | 17 |
| issue: | 1 |
| More Information: | 134, 138 |
| Appears in Collections: | 2017 |
Files in This Item:
| File | Size | Format | |
|---|---|---|---|
| 7728000.pdf | 1.07 MB | Adobe PDF |