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The Transactions of the Korean Institute of Electrical Engineers

The Transactions of the Korean Institute of Electrical Engineers

ISO Journal TitleTrans. Korean. Inst. Elect. Eng.
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  3. 2025-12 (Vol.74 No.12)
  4. 10.5370/KIEE.2025.74.12.2447
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References

1 
J. Xue, 2009, A New Method of Fault Diagnosis for High Voltage Circuit Breakers Based on Vibration SignalsDOI
2 
C. Liu, 2024, Fault Diagnosis of Circuit Breaker Vibration Signals Based on MTF + CNNDOI
3 
A. Janssen, D. Makareinis, C.-E. Sölver, 2013, International Surveys on Circuit-Breaker Reliability Data for Substation and System Studies, IEEE Transactions on Power Delivery, Vol. 29, No. 2, pp. 808-814DOI
4 
J. Gong, Y. Tan, 2024, State Assessment Method of Circuit Breaker Based on Vibration Characteristic DomainDOI
5 
Z. Wang, 2009, Use Vibration Monitoring to Identify Circuit Breakers for Condition AssessmentDOI
6 
A. Boyaci, O. Becker, I. Amihai, 2021, Vibration Monitoring for Medium-Voltage Circuit Breaker Drives Using Artificial Intelligence, Vol. 2021, No. 6DOI
7 
W. Yi, Y.-H. Park, J. Park, 2025, Vibration Signal based Fault Classification Algorithm for C-GIS Switchgear OperatorGoogle Search
8 
K.-J. Park, Y.-H. Park, 2025, Optimal Sensor Placement for Mode Shape Reconstruction Using Kriging and SEFI, pp. 334-335Google Search
9 
S. Ioffe, C. Szegedy, 2015, Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate ShiftGoogle Search
10 
V. Nair, G. E. Hinton, 2010, Rectified Linear Units Improve Restricted Boltzmann Machines, pp. 807-814Google Search
11 
, 352C34 ICP® AccelerometerDOI
12 
, 353B15 ICP® AccelerometerDOI
13 
D. P. Kingma, J. Ba, 2014, Adam: A Method for Stochastic Optimization, arXiv preprint arXiv:1412.6980Google Search
14 
K. He, X. Zhang, S. Ren, J. Sun, 2016, Deep Residual Learning for Image Recognition, pp. 770-778Google Search
15 
F. Chollet, 2017, Xception: Deep Learning with Depthwise Separable Convolutions, pp. 1251-1258Google Search
16 
Ramprasaath R. Selvaraju, 2017, Grad-cam: Visual explanations from deep networks via gradient-based localization, pp. 618-626Google Search