Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/232658
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:
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7728000.pdf1.07 MBAdobe 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 SizeFormat 
7728000.pdf1.07 MBAdobe 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 SizeFormat 
7728000.pdf1.07 MBAdobe PDF