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- Publisher Website: 10.1109/TII.2021.3083240
- Scopus: eid_2-s2.0-85107189378
- WOS: WOS:000712564700027
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Article: A Kaiser Window-Based S-Transform for Time-Frequency Analysis of Power Quality Signals
Title | A Kaiser Window-Based S-Transform for Time-Frequency Analysis of Power Quality Signals |
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Authors | |
Keywords | Energy concentration Fourier transform Kaiser window KS-transform power quality disturbance time-frequency analysis |
Issue Date | 2022 |
Citation | IEEE Transactions on Industrial Informatics, 2022, v. 18, n. 2, p. 965-975 How to Cite? |
Abstract | The accurate time-fre uenc (TF) ositionin of power quality (PQ) disturbances is the basis of dealing with PQ problems in power systems. To accurately detect PQ disturbances, this article proposes a Kaiser window-based S-transform (KST) that provides better time resolution at fundamental frequency to detect the amplitude information for voltage swell, sag, interrupt, flicker, and better frequency resolution at higher frequencies to detect the frequency of time-varying harmonics and oscillatory transient. Based on short-time Fourier transform and S-transform, KST uses a Kaiser window with the characteristic of inherent optimal energy concentration as the kernel function. The Kaiser window can be adjusted adaptively according to the detection demand of PQ disturbances by the designed control function. This allows KST to easily accommodate different detection requirements at different frequencies. The utilization of Fourier transform ensures that KST can be realized quickly. The complex TF matrix is generated after a signal is transformed by KST, where the column vector is expressed as the distribution of amplitude and phase with time at a certain frequency, and the row vector represents the distribution of amplitude and phase with frequency at a certain sampling time. Experimental results demonstrate that the proposed KST significantly outperforms the state-of-the-art techniques in TF analysis of PQ signals, especially for the energy concentration and the detection of fundamental wave. |
Persistent Identifier | http://hdl.handle.net/10722/336283 |
ISSN | 2023 Impact Factor: 11.7 2023 SCImago Journal Rankings: 4.420 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Liang, Chengbin | - |
dc.contributor.author | Teng, Zhaosheng | - |
dc.contributor.author | Li, Jianmin | - |
dc.contributor.author | Yao, Wenxuan | - |
dc.contributor.author | Hu, Shiyan | - |
dc.contributor.author | Yang, Yan | - |
dc.contributor.author | He, Qing | - |
dc.date.accessioned | 2024-01-15T08:25:11Z | - |
dc.date.available | 2024-01-15T08:25:11Z | - |
dc.date.issued | 2022 | - |
dc.identifier.citation | IEEE Transactions on Industrial Informatics, 2022, v. 18, n. 2, p. 965-975 | - |
dc.identifier.issn | 1551-3203 | - |
dc.identifier.uri | http://hdl.handle.net/10722/336283 | - |
dc.description.abstract | The accurate time-fre uenc (TF) ositionin of power quality (PQ) disturbances is the basis of dealing with PQ problems in power systems. To accurately detect PQ disturbances, this article proposes a Kaiser window-based S-transform (KST) that provides better time resolution at fundamental frequency to detect the amplitude information for voltage swell, sag, interrupt, flicker, and better frequency resolution at higher frequencies to detect the frequency of time-varying harmonics and oscillatory transient. Based on short-time Fourier transform and S-transform, KST uses a Kaiser window with the characteristic of inherent optimal energy concentration as the kernel function. The Kaiser window can be adjusted adaptively according to the detection demand of PQ disturbances by the designed control function. This allows KST to easily accommodate different detection requirements at different frequencies. The utilization of Fourier transform ensures that KST can be realized quickly. The complex TF matrix is generated after a signal is transformed by KST, where the column vector is expressed as the distribution of amplitude and phase with time at a certain frequency, and the row vector represents the distribution of amplitude and phase with frequency at a certain sampling time. Experimental results demonstrate that the proposed KST significantly outperforms the state-of-the-art techniques in TF analysis of PQ signals, especially for the energy concentration and the detection of fundamental wave. | - |
dc.language | eng | - |
dc.relation.ispartof | IEEE Transactions on Industrial Informatics | - |
dc.subject | Energy concentration | - |
dc.subject | Fourier transform | - |
dc.subject | Kaiser window | - |
dc.subject | KS-transform | - |
dc.subject | power quality disturbance | - |
dc.subject | time-frequency analysis | - |
dc.title | A Kaiser Window-Based S-Transform for Time-Frequency Analysis of Power Quality Signals | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/TII.2021.3083240 | - |
dc.identifier.scopus | eid_2-s2.0-85107189378 | - |
dc.identifier.volume | 18 | - |
dc.identifier.issue | 2 | - |
dc.identifier.spage | 965 | - |
dc.identifier.epage | 975 | - |
dc.identifier.eissn | 1941-0050 | - |
dc.identifier.isi | WOS:000712564700027 | - |