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2020
Abstract
I. 서론
II. 딥 러닝을 이용한 전동기 고장진단
III. 다중 알고리즘을 이용한 전동기 고장진단
IV. IoT 디바이스, 전동기 고장진단 시스템
V. 결론
REFERENCES
G. Xu, M. Liu, Z. Jiang, W. Shen, and C. Huang, “Online fault diagnosis method based on transfer convolutional neural networks,” IEEE Transactions on Instrumentation and Measurement, vol. 69, no. 2, pp. 509-520, Feb. 2020.
D. J. Choi, J. H. Han, S. U. Park, and S. K. Hong, “Motor fault diagnosis in changed environments using K-means and CNN,” Journal of Institute of Control, Robotics and Systems (in Korean), vol. 26, no. 5, pp. 348-254, May. 2020.
W. Kong, Z. Y. Dong, Y. Jia, D. J. Hill, Y. Xu, and Y. Zhang, “Short-term residential load forecasting based on LSTM recurrent neural network,” IEEE Transactions on Smart Grid, vol. 10, no. 1, pp. 841-851, Jan. 2019.
M. Sundermeyer, H. Ney, and R. Schluter, “From feedforward to recurrent LSTM neural networks for language modeling,” in IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 23, no. 3, pp. 517-529, Mar. 2015.
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