Harmonic and interharmonic detection based on adaptive wavelet and improved EWT
To address the issues of noise sensitivity and over-decomposition when decomposing harmonic signals using empirical wavelet transform （EWT）， a method based on adaptive wavelet denoising and improved EWT is proposed for detecting harmonics and interharmonics. Firstly， to enhance the effectiveness of...
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| Format: | Article |
| Language: | zho |
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zhejiang electric power
2024-11-01
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| Series: | Zhejiang dianli |
| Subjects: | |
| Online Access: | https://zjdl.cbpt.cnki.net/WKE3/WebPublication/paperDigest.aspx?paperID=a29ddf8b-795d-4804-ada5-b49a7dc29f57 |
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| _version_ | 1846157675128160256 |
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| author | KONG Chuirui CHEN Fengxian YANG Lingrui CHE Yukui YANG Haixian XIA Wei GUO Cheng |
| author_facet | KONG Chuirui CHEN Fengxian YANG Lingrui CHE Yukui YANG Haixian XIA Wei GUO Cheng |
| author_sort | KONG Chuirui |
| collection | DOAJ |
| description | To address the issues of noise sensitivity and over-decomposition when decomposing harmonic signals using empirical wavelet transform （EWT）， a method based on adaptive wavelet denoising and improved EWT is proposed for detecting harmonics and interharmonics. Firstly， to enhance the effectiveness of traditional wavelet threshold functions， an adaptive parameterless threshold function is introduced. Then， by analyzing the signal spectrum using EWT， a series of filter banks is obtained to decompose the signal components. Finally， dynamic time warping （DTW） is employed to reconstruct the over-decomposed signals， resulting in the final components and identifying their frequencies and amplitudes. Simulation results demonstrate that the proposed method effectively suppresses noise in the harmonics and improves the over-decomposition of EWT. Comparison with empirical mode decomposition （EMD） and particle swarm optimization based variational mode decomposition （PSO-VMD） verifies the superiority of the proposed method in separating harmonics and detecting interharmonics. |
| format | Article |
| id | doaj-art-94d16e5dc74a4b7f88dbee465c407f74 |
| institution | Kabale University |
| issn | 1007-1881 |
| language | zho |
| publishDate | 2024-11-01 |
| publisher | zhejiang electric power |
| record_format | Article |
| series | Zhejiang dianli |
| spelling | doaj-art-94d16e5dc74a4b7f88dbee465c407f742024-11-25T06:18:02Zzhozhejiang electric powerZhejiang dianli1007-18812024-11-0143119710510.19585/j.zjdl.2024110111007-1881（2024）11-0097-09Harmonic and interharmonic detection based on adaptive wavelet and improved EWTKONG Chuirui0CHEN Fengxian1YANG Lingrui2CHE Yukui3YANG Haixian4XIA Wei5GUO Cheng6Qujing Malong Power Supply of Yunnan Power Grid Co.， Ltd.， Qujing， Yunnan 655100， ChinaQujing Malong Power Supply of Yunnan Power Grid Co.， Ltd.， Qujing， Yunnan 655100， ChinaFaculty of Electric Power Engineering， Kunming University of Science and Technology， Kunming 650500， ChinaQujing Malong Power Supply of Yunnan Power Grid Co.， Ltd.， Qujing， Yunnan 655100， ChinaQujing Malong Power Supply of Yunnan Power Grid Co.， Ltd.， Qujing， Yunnan 655100， ChinaQujing Malong Power Supply of Yunnan Power Grid Co.， Ltd.， Qujing， Yunnan 655100， ChinaFaculty of Electric Power Engineering， Kunming University of Science and Technology， Kunming 650500， ChinaTo address the issues of noise sensitivity and over-decomposition when decomposing harmonic signals using empirical wavelet transform （EWT）， a method based on adaptive wavelet denoising and improved EWT is proposed for detecting harmonics and interharmonics. Firstly， to enhance the effectiveness of traditional wavelet threshold functions， an adaptive parameterless threshold function is introduced. Then， by analyzing the signal spectrum using EWT， a series of filter banks is obtained to decompose the signal components. Finally， dynamic time warping （DTW） is employed to reconstruct the over-decomposed signals， resulting in the final components and identifying their frequencies and amplitudes. Simulation results demonstrate that the proposed method effectively suppresses noise in the harmonics and improves the over-decomposition of EWT. Comparison with empirical mode decomposition （EMD） and particle swarm optimization based variational mode decomposition （PSO-VMD） verifies the superiority of the proposed method in separating harmonics and detecting interharmonics.https://zjdl.cbpt.cnki.net/WKE3/WebPublication/paperDigest.aspx?paperID=a29ddf8b-795d-4804-ada5-b49a7dc29f57harmonicinterharmonicewtwavelet threshold functiondtw |
| spellingShingle | KONG Chuirui CHEN Fengxian YANG Lingrui CHE Yukui YANG Haixian XIA Wei GUO Cheng Harmonic and interharmonic detection based on adaptive wavelet and improved EWT Zhejiang dianli harmonic interharmonic ewt wavelet threshold function dtw |
| title | Harmonic and interharmonic detection based on adaptive wavelet and improved EWT |
| title_full | Harmonic and interharmonic detection based on adaptive wavelet and improved EWT |
| title_fullStr | Harmonic and interharmonic detection based on adaptive wavelet and improved EWT |
| title_full_unstemmed | Harmonic and interharmonic detection based on adaptive wavelet and improved EWT |
| title_short | Harmonic and interharmonic detection based on adaptive wavelet and improved EWT |
| title_sort | harmonic and interharmonic detection based on adaptive wavelet and improved ewt |
| topic | harmonic interharmonic ewt wavelet threshold function dtw |
| url | https://zjdl.cbpt.cnki.net/WKE3/WebPublication/paperDigest.aspx?paperID=a29ddf8b-795d-4804-ada5-b49a7dc29f57 |
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