Defect Diagnosis Method of Cable Shielding Layer Based on Frequency Domain Reflection Coefficient Spectrum

Zhao, Hai Ming; Zhang, Haotian; Su, Guowen; Shi, Xudong

doi:10.1109/temc.2022.3213351

Cited by 3 publications

(1 citation statement)

References 21 publications

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“…The presence of local defects and fault points in the cable can cause changes in its physical parameters, leading to changes in local characteristic impedance, resulting in impedance mismatch and the formation of some impedance mismatch points. This leads to the generation of reflection waves carrying defect feature information at impedance mismatch points during traveling wave transmission, these reflections will be reflected in the broadband impedance spectrum of the cable [17,18].…”

Section: Cable Distribution Parameter Modelmentioning

confidence: 99%

Research on cable fault detection method based on attenuation compensation technology

Chen,

Bi,

Qiu

et al. 2024

Eighth International Conference on Energy System, Electricity, and Power (ESEP 2023)

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Frequency domain reflection (FDR) is a powerful method for detecting impedance discontinuity points such as local defects and faults in power cables. However, due to signal attenuation, the reflection formed by faults and defects will weaken with increasing distance, which poses a significant challenge for achieving precise cable detection. To address this issue, this article proposes a attenuation compensation technology based on FDR, aiming to compensate for signal attenuation and improve detection accuracy and sensitivity. A cable fault simulation model and experimental platform have been established to verify the effectiveness of this method. The results show that the positioning error of this method is less than 0.5%, and the average error of transmission parameter recovery is less than 5%, verifying the effectiveness of this method

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Section: Cable Distribution Parameter Modelmentioning

confidence: 99%

Research on cable fault detection method based on attenuation compensation technology

Chen,

Bi,

Qiu

et al. 2024

Eighth International Conference on Energy System, Electricity, and Power (ESEP 2023)

View full text Add to dashboard Cite

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Novel Parameter Identification Method of Extended Debye Model for Long-Length Submarine Cables

Lin,

Zhou,

2024

IEEE Trans. Dielect. Electr. Insul.

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Short-term wind power prediction and uncertainty analysis based on VDM-TCN and EM-GMM

Peng,

Zuo,

et al. 2024

Front. Energy Res.

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Due to the fluctuating and intermittent nature of wind energy, its prediction is uncertain. Hence, this paper suggests a method for predicting wind power in the short term and analyzing uncertainty using the VDM-TCN approach. This method first uses Variational Mode Decomposition (VDM) to process the data, and then utilizes the temporal characteristics of Temporal Convolutional Neural Network (TCN) to learn and predict the dataset after VDM processing. Through comparative experiments, we found that VDM-TCN performs the best in short-term wind power prediction. In wind power prediction for 4-h and 24-h horizons, the RMSE errors were 1.499% and 4.4518% respectively, demonstrating the superiority of VDM-TCN. Meanwhile, the Gaussian Mixture Model (GMM) can effectively quantify the uncertainty of wind power generation at different time scales.

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Defect Diagnosis Method of Cable Shielding Layer Based on Frequency Domain Reflection Coefficient Spectrum

Cited by 3 publications

References 21 publications

Research on cable fault detection method based on attenuation compensation technology

Research on cable fault detection method based on attenuation compensation technology

Novel Parameter Identification Method of Extended Debye Model for Long-Length Submarine Cables

Short-term wind power prediction and uncertainty analysis based on VDM-TCN and EM-GMM

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