Noise Reduction Method for Partial Discharge Fluorescence Fiber Sensors Based on Optimized Empirical Wavelet Transform
A novel self-adaptive denoising method utilizing optimized empirical wavelet transform (EWT) is proposed to enhance the sensitivity of partial discharge (PD) fluorescence fiber sensors. The optimized EWT enhances the spectrum segmentation capability of conventional EWT via spectral kurtosis (SK). Th...
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| Format: | Article |
| Language: | English |
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IEEE
2024-01-01
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| Series: | IEEE Photonics Journal |
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| Online Access: | https://ieeexplore.ieee.org/document/10588988/ |
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| author | Chengyong Hu Yi Huang Chuanlu Deng Ming Jia Qi Zhang Peng Wu Yuncai Lu Qun Li Xiaobei Zhang Tingyun Wang |
| author_facet | Chengyong Hu Yi Huang Chuanlu Deng Ming Jia Qi Zhang Peng Wu Yuncai Lu Qun Li Xiaobei Zhang Tingyun Wang |
| author_sort | Chengyong Hu |
| collection | DOAJ |
| description | A novel self-adaptive denoising method utilizing optimized empirical wavelet transform (EWT) is proposed to enhance the sensitivity of partial discharge (PD) fluorescence fiber sensors. The optimized EWT enhances the spectrum segmentation capability of conventional EWT via spectral kurtosis (SK). The SK at the optimal window length of noisy PD fluorescence signal is calculated to determine compact support of the Fourier spectrum for subsequent signal decomposition. Frequency components with SK value over the statistic threshold are used to rebuild the PD fluorescence signal. Subsequently, residual noise in the reconstructed signal is removed through adaptive wavelet threshold denoising. To evaluate the performance of the proposed method in denoising numerically simulated and experimentally obtained noisy PD fluorescence signals, outcomes are compared to those of the novel adaptive ensemble empirical mode decomposition (NAEEMD) method, EWT method, EWT joint with kurtogram (KEWT) method, and correlation spectral negentropy (CSNE)-based method. Quantitative metrics and running time are used to assess denoising performance and execution efficiency, respectively. Simulated and experimental results demonstrate that the proposed method possesses a superior noise reduction effect compared to the other four methods while restoring the detail of the PD fluorescence signal flooded by serious noise and consuming reduced computational cost. |
| format | Article |
| id | doaj-art-26f32067f57e4b799996613ba25bb2a6 |
| institution | DOAJ |
| issn | 1943-0655 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Photonics Journal |
| spelling | doaj-art-26f32067f57e4b799996613ba25bb2a62025-08-20T03:07:27ZengIEEEIEEE Photonics Journal1943-06552024-01-011641910.1109/JPHOT.2024.342443910588988Noise Reduction Method for Partial Discharge Fluorescence Fiber Sensors Based on Optimized Empirical Wavelet TransformChengyong Hu0https://orcid.org/0000-0003-0026-3997Yi Huang1https://orcid.org/0000-0002-4381-6291Chuanlu Deng2https://orcid.org/0009-0007-6497-2430Ming Jia3Qi Zhang4https://orcid.org/0000-0002-6865-5981Peng Wu5Yuncai Lu6Qun Li7Xiaobei Zhang8https://orcid.org/0000-0002-9228-8720Tingyun Wang9https://orcid.org/0000-0002-9106-3087Key Laboratory of Specialty Fiber Optics and Optical Access Networks, Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication, Shanghai University, Shanghai, ChinaKey Laboratory of Specialty Fiber Optics and Optical Access Networks, Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication, Shanghai University, Shanghai, ChinaKey Laboratory of Specialty Fiber Optics and Optical Access Networks, Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication, Shanghai University, Shanghai, ChinaKey Laboratory of Specialty Fiber Optics and Optical Access Networks, Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication, Shanghai University, Shanghai, ChinaKey Laboratory of Specialty Fiber Optics and Optical Access Networks, Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication, Shanghai University, Shanghai, ChinaState Grid Jiangsu Electric Power Research Institute, Nanjing, ChinaState Grid Jiangsu Electric Power Research Institute, Nanjing, ChinaState Grid Jiangsu Electric Power Research Institute, Nanjing, ChinaKey Laboratory of Specialty Fiber Optics and Optical Access Networks, Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication, Shanghai University, Shanghai, ChinaKey Laboratory of Specialty Fiber Optics and Optical Access Networks, Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication, Shanghai University, Shanghai, ChinaA novel self-adaptive denoising method utilizing optimized empirical wavelet transform (EWT) is proposed to enhance the sensitivity of partial discharge (PD) fluorescence fiber sensors. The optimized EWT enhances the spectrum segmentation capability of conventional EWT via spectral kurtosis (SK). The SK at the optimal window length of noisy PD fluorescence signal is calculated to determine compact support of the Fourier spectrum for subsequent signal decomposition. Frequency components with SK value over the statistic threshold are used to rebuild the PD fluorescence signal. Subsequently, residual noise in the reconstructed signal is removed through adaptive wavelet threshold denoising. To evaluate the performance of the proposed method in denoising numerically simulated and experimentally obtained noisy PD fluorescence signals, outcomes are compared to those of the novel adaptive ensemble empirical mode decomposition (NAEEMD) method, EWT method, EWT joint with kurtogram (KEWT) method, and correlation spectral negentropy (CSNE)-based method. Quantitative metrics and running time are used to assess denoising performance and execution efficiency, respectively. Simulated and experimental results demonstrate that the proposed method possesses a superior noise reduction effect compared to the other four methods while restoring the detail of the PD fluorescence signal flooded by serious noise and consuming reduced computational cost.https://ieeexplore.ieee.org/document/10588988/Fluorescence fiber sensorspartial discharge detectionsignal denoisingempirical wavelet transform (EWT)spectral kurtosis (SK) |
| spellingShingle | Chengyong Hu Yi Huang Chuanlu Deng Ming Jia Qi Zhang Peng Wu Yuncai Lu Qun Li Xiaobei Zhang Tingyun Wang Noise Reduction Method for Partial Discharge Fluorescence Fiber Sensors Based on Optimized Empirical Wavelet Transform IEEE Photonics Journal Fluorescence fiber sensors partial discharge detection signal denoising empirical wavelet transform (EWT) spectral kurtosis (SK) |
| title | Noise Reduction Method for Partial Discharge Fluorescence Fiber Sensors Based on Optimized Empirical Wavelet Transform |
| title_full | Noise Reduction Method for Partial Discharge Fluorescence Fiber Sensors Based on Optimized Empirical Wavelet Transform |
| title_fullStr | Noise Reduction Method for Partial Discharge Fluorescence Fiber Sensors Based on Optimized Empirical Wavelet Transform |
| title_full_unstemmed | Noise Reduction Method for Partial Discharge Fluorescence Fiber Sensors Based on Optimized Empirical Wavelet Transform |
| title_short | Noise Reduction Method for Partial Discharge Fluorescence Fiber Sensors Based on Optimized Empirical Wavelet Transform |
| title_sort | noise reduction method for partial discharge fluorescence fiber sensors based on optimized empirical wavelet transform |
| topic | Fluorescence fiber sensors partial discharge detection signal denoising empirical wavelet transform (EWT) spectral kurtosis (SK) |
| url | https://ieeexplore.ieee.org/document/10588988/ |
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