Prediction of Incipient Faults in Underground Power Cables Utilizing S-Transform and Support Vector Regression
Author:
Publisher
School of Electrical Engineering and Informatics (STEI) ITB
Subject
General Engineering
Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Detection and Identification of Underground Cable Incipient Faults Based on Denoising Autoencoder and Optimized Convolutional Neural Network;2023 International Conference on Power System Technology (PowerCon);2023-09-21
2. Transform Waveforms Into Signature Vectors for General-Purpose Incipient Fault Detection;IEEE Transactions on Power Delivery;2022-12
3. Latent Fault Detection Method for Medium Voltage Cables Based on Kizilcay Arc Model and KNN;2021 IEEE 2nd China International Youth Conference on Electrical Engineering (CIYCEE);2021-12-15
4. Analysis of a Practical Study for Under-Ground Cable Faults Causes;2021 22nd International Middle East Power Systems Conference (MEPCON);2021-12-14
5. A similarity-based framework for incipient fault detection in underground power cables;International Journal of Electrical Power & Energy Systems;2021-12
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