TY - JOUR
T1 - Condition Monitoring of 154 kV HTS Cable Systems via Temporal Sliding LSTM Networks
AU - Lee, Geon Seok
AU - Bang, Su Sik
AU - Mantooth, Homer Alan
AU - Shin, Yong June
N1 - Publisher Copyright:
© 2013 IEEE.
PY - 2020
Y1 - 2020
N2 - Higherature superconducting (HTS) cables are expected to be installed in cable tunnels that are already constructed in urban districts. Therefore, the installation of normal joint boxes is inevitable, and it is necessary to develop a diagnostic methodology that considers both the existence of the joints and the electrical characteristics of HTS cables. In this work, temporal sliding long short-term memory (TS-LSTM) is proposed to estimate the locations of the joints that can be hidden by multiple reflections. TS-LSTM includes short-term TS-LSTM and long-term TS-LSTM for analyzing various time dependencies. The reflected signals of the actual joints, which are distinguished from multiple reflections, are analyzed via the chirplet transform (CT) which is one of the time-frequency (TF) analysis methods. The proposed condition monitoring method is applied to an AC 154 kV 600 MVA HTS cable system (1 km) connected to a real power grid network in Jeju, South Korea. For the validation of the proposed methodology, the dielectric and electrical characteristics of the 154 kV HTS cable system are monitored during the cooling process.
AB - Higherature superconducting (HTS) cables are expected to be installed in cable tunnels that are already constructed in urban districts. Therefore, the installation of normal joint boxes is inevitable, and it is necessary to develop a diagnostic methodology that considers both the existence of the joints and the electrical characteristics of HTS cables. In this work, temporal sliding long short-term memory (TS-LSTM) is proposed to estimate the locations of the joints that can be hidden by multiple reflections. TS-LSTM includes short-term TS-LSTM and long-term TS-LSTM for analyzing various time dependencies. The reflected signals of the actual joints, which are distinguished from multiple reflections, are analyzed via the chirplet transform (CT) which is one of the time-frequency (TF) analysis methods. The proposed condition monitoring method is applied to an AC 154 kV 600 MVA HTS cable system (1 km) connected to a real power grid network in Jeju, South Korea. For the validation of the proposed methodology, the dielectric and electrical characteristics of the 154 kV HTS cable system are monitored during the cooling process.
KW - Condition monitoring
KW - long short-term memory (LSTM)
KW - superconducting cable
KW - temporal sliding LSTM (TS-LSTM) networks
KW - time-frequency analysis
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U2 - 10.1109/ACCESS.2020.3014227
DO - 10.1109/ACCESS.2020.3014227
M3 - Article
AN - SCOPUS:85089937882
SN - 2169-3536
VL - 8
SP - 144352
EP - 144361
JO - IEEE Access
JF - IEEE Access
M1 - 9157858
ER -